Prediction markets aggregate information

Prediction markets, like the stock market, aggregate expert knowledge and public and semi-public information. If the probability of an event is different than what is reflected in the price, people will bet to make a profit. Their bets will move the prediction market price toward the “correct” value. If the probability changes due to new information, the prediction market price will quickly adjust. If the market is mature and the number of contracts is large, experts have a financial incentive to participate and the market price should be an accurate real-time estimate of the probability of the event. This estimate –and its responsiveness to information – is the key source of business value.

Using prediction markets for crisis preparation and management

To understand the potential of prediction markets for crisis preparation and management, consider current geopolitical uncertainty. For example, many business decisions depend on North American trade and tariffs. Board and CEOs will want assurance that the company will be able to manage all the ramifications of USMCA scenarios, up to and including a full US exit. For many companies, however, going beyond a high-level analysis would be difficult and time-consuming and implementing full mitigation would be quite costly. The leadership could set “DefCon” levels [similar to the U.S. military’s readiness alert system], with higher risk triggering more aggressive and painful mitigation efforts. If the prediction markets are active, the probability of particular USMCA outcomes would be an excellent objective real-time signal for triggering the appropriate response.

This is not an isolated case. Whenever a change in the probability of an event would trigger a decision or action, a corresponding prediction market would be valuable information. This is true both of events that occur – Trump’s election or Russia’s invasion of Ukraine – and fears that do not materialize, like the collapse of the Euro in 2012 or a Korea crisis in 2018.

Probabilities from prediction markets could also improve scenario analysis and wargaming. If a consequential event has high enough probability of occurring (say at least 10%) that would be the signal to do a scenario analysis of the event, with the probability also helping mitigation decisions.

Improving forecasts with prediction markets

Decisions on product programs, capacity investments, hiring, and business plans all rely on forecasts of industry volume, market share, pricing, and costs. Too often these forecasts have an optimistic bias, reflecting pressure on the forecasters and leaders to meet targets and get funding approved. There is also a bias towards smooth growth, discounting disruptive events or technologies. Five-year plans often look like hockey sticks, with conservative estimates for the budget year (so that bonus targets are reached) and bright optimism beyond. The next year the hockey stick has moved out a year.

Public prediction markets might help correct some of the bias, particularly as the number of contracts and market participants increases. A market forecast of U.S. vehicle or full-size truck sales in 2027 or 2030 could help automakers and suppliers plan. Probabilities of election outcomes or high oil prices or a Taiwan invasion could help select and calibrate stress-test scenarios. One challenge to such applications is that the event contract might not exist for many risks relevant to the company, particularly for the longer horizon of investment decisions. Companies should experiment with establishing event contracts tied to information they need in decision-making.

Internal prediction markets

Public markets could be supplemented with internal “markets”. Employees could place bets, for example, on whether or not a particular market share would be achieved. While such markets could potentially overcome bias, there would be challenges to making it work. Companies would need to worry about insider trading or market manipulation or distorting individual incentives for company success. The best use-case might be an external event where there is diffuse insight within the company. For example, “will the new product launch of a leading competitor increase its market share by more than 1 point next year.” Companies might want to pilot an internal market with a group of internal experts.

Concerns with prediction markets

The growth of prediction markets has raised understandable and appropriate concerns about rules, regulatory arbitrage, insider trading, and market manipulation. The indictment of a U.S. soldier for allegedly profiting from insider information on the Venezuela operation is only one instance. But for a business using prediction markets for information rather than to make bets, insider trading is not a concern. Kalshi is currently regulated by the CFTC though the rules are in flux, while Polymarket is currently outside U.S. jurisdiction. Congress and states are trying to establish rules and guardrails. The inevitable increase in oversight and regulation of these markets will be good news for the same reason it is in the stock market; it will increase trust and transparency, encouraging wide participation.

The Bottom Line

Using the power of markets to find the probabilities of events is an important advance. Businesses should try to develop markets in event probabilities that could affect decisions. As prediction markets mature, they should monitor developments with the goal of leveraging this innovative information source.

Welcome to the May issue of The Briefing Table where we review each month’s major events from a strategic and risk management perspective.

April was a month where a familiar pattern reasserted itself. A ceasefire that was supposed to restore normal conditions didn’t. A tariff deadline that was supposed to be about pharmaceutical companies turned out to affect almost every large employer in the country. An AI model arrived that its own developer deemed too dangerous to release. A regulatory deadline that had been on the calendar for two years became a deal-room variable. And a Federal Reserve succession that was supposed to be a procedural formality became the first fully partisan confirmation vote for a Fed chair in American history.

These five forces, each a deferred cost arriving on a compressed timeline, are the subject of this issue.

1) Anthropic Mythos: The Threat That Wasn’t Supposed to Arrive This Year

Ask most CIOs what they expected from AI and cybersecurity in 2026, and the answer would have been incremental. A genuine capability breakthrough, serious enough to prompt a major AI lab to withhold a model from the public entirely, was not in the forecast.

It arrived anyway.

On April 7^th, Anthropic announced Claude Mythos Preview and declined to release it publicly. Whereas OpenAI’s temporary suppression of GPT-2 in 2019 was widely derided as theatrical, no one is mocking Anthropic. During testing, Mythos identified and exploited zero-day vulnerabilities across every major operating system and browser, including bugs that had survived decades of human review. The UK’s AI Security Institute found it succeeded at expert-level hacking tasks 73% of the time. One year ago, no AI model could complete those tasks at all.

In response, Anthropic launched Project Glasswing, committing $100M in usage credits to let AWS, Cisco, CrowdStrike, and forty other organizations use Mythos defensively to scan critical infrastructure before adversaries could exploit the same capabilities. Anthropic did not train Mythos to have offensive security capabilities. They emerged from general improvements in reasoning and code, which means every subsequent frontier model will have them whether its developer intends it to or not. The controlled release window is also shorter than it appears: independent researchers have shown open-weight models just three to five months behind the frontier can replicate much of the same analysis. U.S. regulators have drawn their own conclusion and are already urging major financial institutions to begin controlled testing now.

The temptation is to file this under “cybersecurity” and hand it to the CISO. That would be a mistake. Mythos-class discovery will flood enterprise vulnerability queues with findings that security teams have no additional capacity to remediate. More acutely, the agentic systems companies are deploying to automate workflows are now the most valuable targets for adversaries. A single prompt injection can co-opt an organization’s highest-privileged digital actor. Last month’s issue argued that the risk in agentic AI is in what agents do, not what they are. Mythos makes that argument viscerally. Ungoverned agents are unlocked doors, and the lockpicks just got dramatically better.

There is also a competitive dimension many C-Suite executives are missing entirely. The organizations currently using Mythos-class capabilities defensively are building a security posture their peers will not have for another year or two. This is the same structural dynamic that played out with every previous generation of security infrastructure. The firms that built the capability before the breaches gained lasting advantages. The ones that waited explained the gap to senior executives. The window to be the former rather than the latter is open now. It will not remain so.

Bottom Line: Commission an agentic AI inventory audit now; what agents are running, what systems they can access, what actions they can take without human review. The organizations that act in the next ninety days will be the ones that don’t have to explain why they didn’t.

2) Pharmaceutical Tariffs: This Is Not a Healthcare Story

Most coverage of the April 2^nd pharmaceutical tariff proclamation has treated it as a healthcare sector story. It is not. It is an employer story, a supply chain story, and a strategic optionality story with a deadline.

Under Section 232, the administration imposed 100% tariffs on imported patented pharmaceuticals and APIs, effective July 31st for large companies. The structure rewards speed: a 0% rate through 2029 for a MFN pricing agreement with HHS and a domestic onshoring plan with Commerce versus 20% for an onshoring plan only. Do neither and face 100%. This is the sectoral escalation we previewed in February’s edition under “The End of Emergency Tariffs.” Parallel Section 232 investigations are already underway in medical consumables, devices, and robotics – i.e., the pharmaceutical action is a template, not a one-off.

Importantly, the MFN/onshoring path is not a compliance exercise. It is a negotiation, and the tariff framework is effectively offering a four-year subsidy, zero tariff liability, in exchange for policy alignment. Organizations recognizing this and moving first will secure favorable terms. Those treating it as a burden to manage will pay the default rate. In addition, the majority of large U.S. companies self-insure their health benefits. Specialty biologics and patented therapies facing the 100% default represent a disproportionate share of those plans’ costs. This is a human capital cost problem, not a healthcare problem, and it arrives before year-end.

Bottom Line: Three parallel tracks: classify your exposure across patented pharmaceuticals and APIs; assess the MFN/onshoring compliance path, because the zero-rate tier requires simultaneous engagement with two federal agencies before July 31; and complete the supply chain audit begun in April; Chinese and Indian API production is a dependency as significant as Gulf-region helium and sulfur.

3) The Iran Ceasefire: Beijing Is the Story Now

Last month, we wrote: “Do not treat a sudden ceasefire as a return to normal.” A ceasefire arrived within two weeks and has been violated by both parties. As of publication, Iran submitted a formal proposal to reopen the Strait in exchange for the U.S. lifting its naval blockade, while deferring nuclear discussions, but Washington effectively rejected it. Meanwhile, Pakistan has stood down the security infrastructure it assembled for a second round of talks and there is no next meeting scheduled. The new baseline is not a ceasefire but a siege.

Just below the surface, a new regional power structure is taking shape. China did not merely benefit from this conflict. It is now shaping its resolution. Beijing’s co-mediator role in Islamabad was confirmed by the White House. Iran’s oil exports have been settled increasingly in renminbi throughout, a practical arrangement not reverting when hostilities end. The country helping end a war earns diplomatic capital persisting for years. China is accumulating it while the United States absorbs the costs.

Jeff Sachs observed in his April interview with C-Suite that the dollar’s share of global reserve holdings has been declining for two decades and that the pace is accelerating. The Iran conflict has now added a live demonstration that the renminbi can function as a credible settlement currency in the world’s most strategically sensitive energy corridor. Sachs’s projection - renminbi exceeding 20% of international trade settlement within a decade, the dollar falling below 50% - now feels less like a long-range forecast and more like an extrapolation of something already in progress. The right move for corporate treasurers, he advised, is to begin building renminbi-denominated banking capacity now. China’s central role in the ceasefire process makes the timeline feel urgent in a way that abstract reserve currency projections do not.

The practical prescription is the one from last month, now sharper: build explicitly for both endpoints. A rapid normalization would compress oil prices, normalize shipping, and release Gulf sovereign wealth into global markets. The 14% intraday swing in early April showed how fast transitions happen. The side you are not prepared for is the one that will cost you.

Bottom Line: The Iran story has two chapters. The first has been modeled: Hormuz disruption, energy costs, supply chain exposure. The second typically has not: China as indispensable regional broker, renminbi advancing in energy settlement, dollar primacy eroding in the one market where it was most entrenched. It should be.

4) The EU AI Act: Already a Valuation Variable

The EU AI Act’s August 2^nd enforcement deadline is now approximately 100 days out, and European deal rooms are already pricing compliance posture into transactions. One Q1 transaction closed at a €7 million discount written into the SPA as a specific AI Act indemnity. One HR analytics asset was pulled from market after four bidders flagged the same Annex III gap. An Austrian lender commanded a two-turn valuation premium because its credit model had been documented against Article 10 since late 2024.

High-risk categories, including hiring, credit, biometric identification, and critical infrastructure, require conformity assessments, technical documentation, CE marking, and EU database registration before August 2nd, with penalties reaching €15 million or 3% of global turnover. The Act applies extraterritorially.

Over half of organizations still lack systematic AI inventories. Without an inventory, risk classification is impossible. Conformity assessment takes six to twelve months. The arithmetic is unambiguous for anyone who has not started.

For organizations conducting M&A or operating in EU-regulated sectors, the compliance posture is no longer a legal question. It is a valuation question. And it lands on the same workforce managing every other demand in this issue. This publication’s March interview with Sponge Group found roughly 60% of employees describe themselves as ‘okay’ or ‘indifferent’ - what they called ‘Generation Numb’ - with change capacity quietly depleted across the organization. The executives who will deliver AI Act readiness within 100 days are not those who issue another mandate from the top. They are those who give their teams agency in how it gets done.

Bottom Line: Start with the inventory. For M&A teams, the question to every diligence counterparty is: show me your AI registry and risk classification. The difference between a two-turn premium and a seven-figure indemnity is documentation that either exists or doesn’t.

The Fed: A Convention Has Ended

Every Fed chair confirmation has included bipartisan support. That norm is gone now, with Kevin Warsh clearing the Senate Banking Committee on April 29^th on a straight party-line vote, enabled by the DOJ’s decision to drop its criminal investigation into incumbent Chairman Powell to clear Senator Tillis’s hold. That sequence set a precedent: threatening a sitting Fed chair with criminal prosecution is now an established executive branch tool. The Fed held rates steady at its final Powell meeting. Futures markets price a largely steady path through 2027. Trump wants 1%. That gap is the uncertainty premium embedded in every capital allocation decision right now.

The Federal Reserve Act is deliberately ambiguous on presidential removal authority. It has rested on political convention: an implicit agreement between both parties that the economic cost of undermining the central bank’s credibility exceeded any short-term political gain. That agreement ended on April 29th. Whether Warsh honors the substance of that convention while the form of it has been broken is now the central question for anyone managing dollar exposure, long-duration assets, or capital allocation decisions that depend on reliable inflation anchoring over the next decade.

Bottom Line: Watch Warsh’s first public statement. Does he frame the Fed’s mission in terms of the president’s agenda or its dual mandate? The former signals a repricing of dollar assets and U.S. sovereign risk. The latter suggests the guardrails held. Either way, five decades of institutional convention ended April 29^th.

Key Take-Aways

• Mythos has crossed a capability threshold the industry didn’t expect this year. The defensive window is months, not years. Ungoverned agents are unlocked doors. Commission the inventory audit.

• Pharmaceutical tariffs are not a healthcare story but a self-insured employer story with a July 31^st deadline. The compliance path is a negotiation with a hidden reward for speed. Start both tracks now.

• The Iran stalemate has hardened into a siege. China is the structural winner. Build for both endpoints as rapid normalization will wrong-foot you as badly as escalation if you’re not prepared.

• The EU AI Act has moved from legal to financial. Deal rooms are already pricing the gap. Start with the inventory. Everything else follows.

• The Fed succession is not a political story. It is a capital markets story. Watch Warsh’s first statement. A five-decade convention ended last week regardless of what he says next.

All five forces share a structure: deferred costs, compressed timelines, stretched execution capacity. The executives who navigate this environment best will be those who see that pattern and build resilience before the next deadline, not after.

In the spring of 2021, a ransomware group called DarkSide broke into Colonial Pipeline’s network through a single compromised password on a legacy VPN account that the company hadn’t known was still active. Within hours, 5,500 miles of fuel pipeline serving the U.S. East Coast went offline. Gas stations ran dry from Virginia to Florida. The CEO called the White House. Colonial paid $4.4 million in ransom, in Bitcoin, within 24 hours of the attack.

DarkSide didn’t need sophisticated AI to pull this off. They needed one unpatched gap in a sprawling, underdocumented legacy system. Now imagine what they could do with it.

AI has just handed attackers a capability that changes the game: the ability to scan millions of lines of code, including decades of custom, undocumented legacy code, and identify exploitable vulnerabilities at machine speed. At the same time, the very same AI tools that create this threat are reshaping how companies build products, manage data, and run operations. Companies that don’t deploy them will fall behind. Companies that do will expand their attack surface. There is no path that avoids both risks simultaneously.

What does this mean for senior business executives?

§AI has triggered a step-function increase in cybersecurity risk on three distinct vectors: AI’s ability to discover and exploit software vulnerabilities, the data security risks embedded in AI agents, and the speed at which AI writes code that may not be secure.

§ The tension is structural, not solvable. The same AI capabilities that create new vulnerabilities also create competitive value. Companies that try to eliminate AI cybersecurity risk entirely will simply be outcompeted. The question is not whether to accept risk, but which risks to accept, and where.

§ Large, established companies face a structural cybersecurity disadvantage relative to startups that investment alone cannot overcome. This is not a temporary gap. It is a permanent feature of competing with decades of accumulated technical debt.

§ The right response is triage: identify mission-critical systems and data, concentrate defenses accordingly, and elevate these decisions from the CISO’s office to the boardroom, where they belong.

Three Vectors of AI Cyber Risk

Cybersecurity risk has always been a fact of corporate life. What has changed is the magnitude, the speed, and, most importantly, the structural nature of the threat. AI has not simply made existing attacks easier. It has opened attack surfaces that were previously unmappable, enabled new categories of intrusion, and done so at precisely the moment when companies are most aggressively expanding those surfaces in pursuit of competitive advantage. Three vectors account for most of the new exposure.

1. AI-Powered Vulnerability Discovery

Anthropic recently revealed that its Mythos AI model is extraordinarily capable at identifying and potentially exploiting security flaws in software, having found vulnerabilities in every system it tested. The announcement was striking enough that Anthropic initially restricted Mythos to a handful of companies, including Microsoft and Google, so they could use it defensively: racing to find and fix their own flaws before the model fell into other hands.

That containment has already begun to erode. Unauthorized users claim to have accessed Mythos, and other AI companies and governments have developed comparable capabilities, or will very shortly. The target space is staggeringly large and, for most enterprises, effectively unmappable: decades of custom, undocumented code whose vulnerabilities have never been systematically catalogued, let alone remediated. AI models can scan this code for weaknesses far faster than any security team can respond. The Colonial Pipeline attackers found one forgotten door. AI-powered tools can try every door simultaneously.

2. The AI Agent “Lethal Trifecta”

AI agents, tools that can autonomously research, analyze, and act on user requests, introduce a different and less understood class of risk. Security researcher Simon Willison describes a “lethal trifecta” of agent capabilities that, when combined, create a reliable attack pathway: access to private data, exposure to untrusted content, and the ability to communicate externally. Any agent that combines all three can be manipulated by an attacker into accessing your private data and sending it outside the organization. The attacker need not penetrate your perimeter. They simply need to trick your agent.

The uncomfortable arithmetic: the risk grows in direct proportion to how useful the agent is. Some tech companies have already given AI agents complete access to internal systems, including email. The more data an agent can reach, the more productive it becomes, and the more catastrophic a breach becomes. As agents proliferate and employees grow more skilled in using them, the exposure compounds. The very behavior that makes agents powerful, autonomous action across large, integrated datasets, is precisely what makes them dangerous if compromised.

3. AI-Generated Code and the Velocity Problem

Services like Claude Code are already capable of writing production-quality code at a pace no human team can match, and capabilities are improving rapidly. Companies that insist on purely human-written code will fall behind. But speed and security are in tension. Code written rapidly and at volume is not necessarily secure. The pace of new code creation can, and in many companies already does, outrun the ability of security teams to audit it. The result is an attack surface that expands from the inside, driven not by attackers but by the company’s own development velocity.

The Legacy Disadvantage: A Gap That Cannot Be Closed

The Colonial Pipeline attack is instructive not because it was sophisticated - it wasn’t - but because it illustrated a structural truth about large, established companies: their accumulated technical debt is an attack surface that grows faster than it can be managed, even without AI. DarkSide didn’t breach Colonial’s state-of-the-art systems. They found a forgotten door that had been left unlocked, probably for years, by people who no longer worked there.

Now consider what AI-powered vulnerability scanning does to that equation. A typical legacy enterprise carries tens of millions of lines of custom code, accumulated over three or four decades, written by developers long since departed, documented incompletely if at all. Previously, finding exploitable vulnerabilities in that environment required skilled human attackers investing significant time. AI tools can now scan that entire codebase in hours and surface a prioritized list of weaknesses. The 2024 Change Healthcare breach, which compromised medical records for nearly one in three Americans and has cost UnitedHealth Group an estimated $3.1 billion in its first year of remediation, was enabled by precisely this kind of legacy exposure: a portal that lacked multi-factor authentication. A forgotten door, again.

The critical distinction is between an operational gap and a structural one. An operational gap, such as insufficient investment, inadequate staffing, or poor processes, can be closed with resources and management attention. A structural gap cannot, at least not fully. Startups build on modern cloud infrastructure with security baked in from day one. They have smaller, better-documented codebases with no forgotten VPN accounts, no legacy portals, no decade-old integrations nobody fully understands anymore. Legacy enterprises cannot replicate these conditions regardless of how much they spend. They can remediate known vulnerabilities, modernize specific systems, and build stronger detection and response capabilities. But the underlying reality, a vast, partially unmappable attack surface that AI-powered tools can probe faster than security teams can defend, does not fundamentally change.

The appropriate board response is neither denial nor despair. It is clear-eyed acceptance of the structural reality, followed by deliberate, prioritized risk management.

Which Industries Face the Sharpest Exposure

AI-driven cybersecurity risk is not uniformly distributed. Four sectors face a materially elevated threat profile, each for structural rather than incidental reasons.

• Healthcare and life sciences face the most acute combination of legacy infrastructure, high-value data, and regulatory consequence. Electronic health record systems at many large hospital networks were built on architectures that predate modern security standards by decades. Patient data commands premium prices in criminal markets: a complete medical record is worth multiples of a credit card number, and every successful breach triggers mandatory public notification. Change Healthcare demonstrated that a single compromised third-party system can cascade into industry-wide disruption of extraordinary scale.

• Financial services carry deep legacy exposure in core banking and payments infrastructure. Some large institutions still run COBOL-based mainframes written before most of their current employees were born. The sector also faces the agent data aggregation risk acutely: AI tools that synthesize transaction histories, credit profiles, and customer communications are enormously valuable for fraud detection and personalization, and enormously dangerous if compromised. Post-breach regulatory accountability now routinely reaches above the CISO level.

• Critical infrastructure, including energy, utilities, and transportation, faces a threat that extends beyond data breach into physical consequence. Operational technology systems controlling pipelines, power grids, and water treatment facilities were designed for reliability, not cybersecurity, and many were never intended to be networked at all. The convergence of IT and OT systems, accelerated by AI-powered monitoring tools, is creating new attack pathways into systems whose compromise carries life-safety implications. Colonial Pipeline was, in hindsight, a warning shot.

• Manufacturing and industrial companies are in the early stages of deploying AI agents across supply chain management, quality control, and production optimization, which puts them squarely in the velocity problem described above. Custom ERP and manufacturing execution systems built over decades create substantial legacy exposure, and competitive pressure to move fast means governance typically lags capability by a year or more. Intellectual property, including product designs, process specifications, and supplier relationships, is an underappreciated target that AI-powered attackers can now pursue systematically.

Other sectors, including retail, professional services, and media, face real exposure as well. But executives in these four industries should treat AI cybersecurity as an immediate board-level priority. Not a medium-term one.

Recommendations for Managing the Heightened Risk

The best strategy starts with two honest recognitions: the inherent risk has increased dramatically, and fully eliminating it is neither possible nor desirable, because the same AI capabilities that create vulnerabilities also create competitive value no company can afford to leave on the table. New security measures are nonetheless urgent. The question is where to concentrate them.

Step Zero: Triage

Before addressing any threat vector, every company needs to know what it is actually protecting. Not all systems carry equal risk, and treating them as though they do wastes resources and creates false security. A breach of marketing analytics is a bad day. A breach of customer health records, operational control systems, or core financial infrastructure can be existential. Identify mission-critical systems and data first, apply a materially higher standard of protection to them, and build the rest of your program around that foundation. In the four high-exposure sectors above, this exercise should already be complete.

Addressing the Three Vectors

• Security vulnerabilities: Use the best available AI model to test your own systems for weaknesses. This is table stakes now, not an advanced practice. Dedicate people to reviewing the findings and acting on them. Because AI models improve continuously and produce different results each time they run, repeat this process regularly for mission-critical systems, weekly for the highest-risk environments. The logic is simple: use the same tools your attackers are using, before they use them on you.

• AI agent data access: Establish and enforce rules governing what data your AI agents can access and whether they can communicate externally. Try to eliminate at least one leg of the lethal trifecta for every agent your employees use. For new deployments, treat the full combination of private data access, untrusted content exposure, and external communication as a disqualifying configuration unless a specific business case justifies it. Consider denying agents access to your most sensitive data entirely, even at some cost to productivity. That tradeoff is usually worth making.

• AI-generated code: Require security review of AI-generated code before it is deployed to systems that touch sensitive data. Where feasible, use AI models to test new code for vulnerabilities before it goes into production, matching AI-speed generation with AI-speed review. The goal is not to slow development. It is to make sure the attack surface does not expand faster than your security team can track it.

Elevate This to the Board

The most consequential governance change required is also the simplest to state: these decisions can no longer be delegated to the CISO. The tradeoffs between AI deployment speed and security exposure, between data aggregation and breach risk, between competitive positioning and risk tolerance, involve revenue, reputation, regulatory exposure, and in some industries, physical safety. They belong at the CEO and board level. Companies that continue to treat cybersecurity as an IT problem will make these tradeoffs poorly, either accepting too much risk in the wrong places or surrendering competitive ground by being too cautious in the right ones.

None of these steps will eliminate AI cybersecurity risk, and they will probably not reduce residual risk to where it was eighteen months ago. But failing to act creates the potential for catastrophic exposure. And excessive caution carries its own risk: falling behind competitors who are moving faster.

The Colonial Pipeline CEO had 24 hours to decide whether to pay $4.4 million in Bitcoin to people he’d never meet, to restore systems his team didn’t fully understand, through a vulnerability nobody had known existed. He paid. None of the risks described in this article are hypothetical. They are extensions of dynamics already in motion, now sharply accelerating. The companies that navigate this environment best will not be those that eliminate the risk. They will be those that understand it clearly enough to make the right tradeoffs, and who make them deliberately, before events make the choices for them.

A July 2025 study from MIT’s Media Lab, Project NANDA, found that roughly 95% of all AI initiatives deliver little or no measurable business value. Not a modest disappointment. Not a case of overblown expectations. Ninety-five percent. More disturbingly, the finding is not even new: an MIT Sloan study back in 2019 found that 40% of companies reported no business gain from machine learning despite significant investment.

What does this mean for senior business executives?

§ AI’s failure is not a technology problem, it is an organizational one. The technology works. Most companies simply don’t know how to deploy it in ways that actually move the needle, and their existing operating models and cultures actively resist the kind of change that would allow them to do so.

§ The potential, however, is enormous and real. Companies that master AI deployment - not experimentation, but genuine at-scale deployment - can expect productivity gains in innovation and R&D of roughly 40%, as well as material improvements in manufacturing quality, supply chain resilience, and customer lifetime value. A handful of early movers are already pulling ahead.

§ Closing the gap requires executives to stop treating AI as a technology initiative and start treating it as an organizational capability: the deliberate combination of technology, process, data, and people aligned around specific, measurable business outcomes.

The Promise Is Real And So Is the Chasm

The skeptics who dismiss AI as yet another overhyped technology cycle are simply wrong. The potential is genuine, it is large, and, in certain domains, nothing short of transformational.

Consider the automotive industry, a useful proxy for large, complex, capital-intensive enterprises. Today, most automakers are capturing incremental AI gains through, for example, engineering copilots, supply chain planning, and in-vehicle personalization. Useful certainly, but not yet the stuff of competitive revolution. The more consequential battlegrounds lie ahead: AI-enabled autonomous vehicle validation, connected-vehicle monetization, and fleet intelligence in the medium term; fully autonomous driving, AI-accelerated materials discovery, and virtual twins replacing physical testing in the longer term. None of this is science fiction. Most of it is already being prototyped. The question is not whether these shifts will happen, but who will be positioned to lead them and who will be left managing the consequences.

More broadly, AI’s strategic role in any enterprise ascends through four layers of increasing consequence. Personal productivity (individual employees using AI assistants) is the entry point. Operational efficiency follows: AI embedded in manufacturing, quality control, and supply chain delivering real cost reduction. Revenue impact comes next, as AI powers personalized experiences, dynamic pricing, and connected-product monetization. At the top sits strategic innovation: AI enabling entirely new products, business models, and industry ecosystems. This is where competitive repositioning actually happens. The trouble is that most companies are still camped on the ground floor, having deployed AI for individual productivity, run a handful of pilots in operations, and called it a day. The upper floors, where the real value lives, remain largely unoccupied.

“AI can unlock roughly 40% productivity gains in innovation and R&D alone. Most companies are leaving nearly all of that on the table.”

The Hard Truth: 95% of AI Initiatives Fail

Here is the reality check that most AI enthusiasts would prefer to skip. For all the investment, for all the pilots, for all the breathless announcements, the overwhelming majority of AI initiatives are not delivering meaningful business impact. The MIT Project NANDA findings are unambiguous: global AI investment has reached $35 billion; 80% of companies report no or minimal AI impact; 95% of AI pilots are generating little or no significant value. Only 5% are getting it right.

This is not primarily a technology problem. The AI itself (the models, the infrastructure, the tools) is already far more capable than most organizations know what to do with. The bottleneck is not the technology. It is the organization. And this pattern, it turns out, is not new at all.

In 1987, Nobel laureate Robert Solow made a quietly devastating observation about the Information Age: “You can see the computer age everywhere but in the productivity statistics.” Decades of investment in transistors, microprocessors, and mainframes had been expected to produce a great surge in productivity, and yet the statistics showed nothing of the kind. The dot-com boom of the 1990s followed the same script at higher velocity: extraordinary technology, extraordinary hype, billions invested, and then the crash of 2000–2001. The Nasdaq lost 78% of its value. Hundreds of companies evaporated. And yet, within a few years, the productivity gains that the skeptics had declared a mirage finally arrived: broad, sustained, and transformational. Amazon, Google, and the modern internet economy were all built in the rubble of the bust. The technology had been real all along. The organizations, the infrastructure, and the business models simply needed time to catch up.

History suggests that what we may be witnessing now has a name. In the diffusion of transformative technologies, initial enthusiasm drives rapid early adoption among pioneers, only to be followed by a dip as the early majority hesitates and disillusionment sets in, before a second, more durable wave of growth eventually materializes. Such “saddle patterns” are far more common than most executives appreciate. In fact, up to half of all high-tech products follow this path, with adoption sometimes dropping by 25% or more during the saddle before recovering.

The current AI moment has the hallmarks of a saddle in progress: extraordinary early momentum, widening disillusionment as the gap between promise and delivery becomes undeniable, and the very real possibility of a near-term correction as inflated valuations, boardroom fatigue, and unmet expectations collide. None of this necessarily means that the underlying technology is flawed or that the long-term transformation is in doubt. It does mean, as it did with the internet at the turn of the century and electric vehicles more recently, that the full realization of the hype is simply taking longer, and demanding more, than the hype itself suggested.

Four failure modes recur with depressing consistency across industries.

The Pilot Factory is probably the most common. Organizations launch dozens of interesting AI experiments, celebrate a few early wins, and then quietly watch the initiatives peter out without ever achieving scale. Pilots become a substitute for deployment rather than a path to it. The organization is perpetually “exploring” AI, which sounds dynamic and innovative but actually means nothing changes.

Tech-led, not Value-led is the second failure mode. AI pilots are designed as technology experiments - testing the capabilities of a new model, validating a use case in the abstract - rather than as value creation experiments with specific business targets, clear ownership, and meaningful accountability. The technology team declares success. The business sees no difference in its P&L.

Data Fragmentation is the silent killer. AI runs on data. Organizations that have spent decades accumulating data in siloed, inconsistent, poorly governed repositories find that their AI tools are only as good as the inputs they receive - which is to say, not very good. Garbage in, garbage out is not a new principle, but AI has a remarkable talent for amplifying it.

The Missing Adoption Engine is the fourth and perhaps most consequential failure mode. Even when AI tools work well, organizations fail to embed them in actual business processes and decisions. Individual employees may use AI assistants sporadically. But the AI is not wired into how decisions are actually made, who is accountable for outcomes, and what the incentives are for using it properly. Without an adoption engine - a deliberate, managed process of embedding AI in the organizational fabric - value evaporates.

Confirming the pattern, the MIT NANDA study found that the top barriers to scaling AI in the enterprise were not technical at all. They were challenging change management, lack of executive sponsorship, poor user experience, and user unwillingness to adopt new tools. The culprits, in short, are leadership, culture, and organization: the same forces that have derailed every major transformation wave before this one, and will derail this one too, for companies that fail to take them seriously. Both things are true simultaneously: the productivity gains are real and will eventually arrive, as they did after the dot-com bust; and most organizations are actively ensuring they will not be the ones to capture them.

Winners Redesign the Organization, Not Just the Technology

The companies that are successfully capturing AI value at scale share one defining characteristic: they have stopped treating AI as a technology initiative and started treating it as an organizational capability and redesign challenge. They are not just buying better tools. They are rebuilding how they work.

The research on what actually drives AI value is striking in its clarity, and its inconvenience. The algorithms themselves account for a relatively small share of the value AI can generate. The technology infrastructure required to deploy them accounts for somewhat more. But the overwhelming majority of the value, the part that actually shows up in the P&L, comes from people and organizational change: new ways of working, behavioral shifts, redesigned workflows, and the cultural transformation required to embed AI in how decisions are actually made. Most organizations are investing their attention and capital in the smaller parts and neglecting the larger one. This is why their results are so consistently disappointing, and why no upgrade in model capability will fix the problem.

The architecture of a genuinely AI-enabled organization rests on three interdependent foundations: a shared data foundation (governed, high-quality, accessible assets spanning the entire value chain, not data warehouses owned by IT and begrudgingly shared with business units); a reusable AI platform that prevents every team from reinventing the wheel and allows successful use cases to scale rather than remain one-off experiments; and, most critically, AI embedded in actual decision-making, not sitting alongside real processes as an optional add-on, but wired into the decisions that drive the business, with clear accountability for outcomes.

Supporting this core are two organizational enablers that many companies underestimate. Ways of working must change: AI deployment requires shorter experimentation cycles, genuine tolerance for failure, and rapid iteration - a cultural shift that can be genuinely jarring for organizations built on the rigorous, long-horizon engineering and planning processes that made them successful in the first place. And talent must evolve: the winning formula pairs deep domain expertise with AI and data talent in cross-functional teams. Not AI specialists working in isolation and presenting findings to skeptical business managers, but genuinely integrated teams where domain knowledge and technical capability reinforce each other.

Holding all of this together is executive leadership, and, specifically, AI literacy at the top. Not deep technical knowledge; C-suite executives do not need to understand transformer architectures. But enough fluency to ask the right questions, make informed investment decisions, sponsor change rather than merely endorse it, and refuse to accept “we’re running lots of pilots” as a satisfying answer to “what value are we creating?”

“The risk is not that AI fails. It is that value shifts outside your organization’s control while you are still running pilots.”

So What? Implications for C-Suite Executives

The gap between AI’s potential and most organizations’ ability to capture it represents both a significant risk and a significant opportunity, and the window for getting it right is narrowing faster than most boards appreciate. The performance difference between companies that have mastered AI deployment and those still running pilots is not modest. Early movers are generating materially higher revenue growth, larger cost reductions, and substantially higher total shareholder returns than their lagging peers, and they are reinvesting those gains into even greater AI capabilities. The gap is not merely widening. It is compounding.

The urgency is further amplified by what is coming next. The current wave of AI (generative tools, copilots, prediction engines) is already being succeeded by a new generation of agentic AI systems capable of planning, reasoning, and executing complex multi-step tasks with minimal human intervention. Agents that resolve customer issues end-to-end, renegotiate supplier contracts in real time, or redesign production schedules autonomously are no longer theoretical. They are being deployed now, and they are delivering EBITDA gains that dwarf what earlier AI waves produced. For organizations that have not yet crossed the threshold from experimentation to scaled deployment, this matters enormously: they risk being not one but two waves behind before they have mastered the first.

The strategic questions that follow are sharper and more urgent than most boards currently appreciate. Where should your organization choose to differentiate: in core products, software, or system intelligence? What proprietary data advantage can you build across your customers, operations, and value chain, and how quickly? Where should you control versus depend on platform providers and ecosystem partners? How does product development transform from discrete programs to continuous learning systems? And how does AI scale beyond isolated pilots into the core of your operations?

These are not technology questions. They are strategy questions. And they have no universal answers. The right response depends on your current position, your proprietary assets, your competitive context, and your organizational capabilities. But refusing to engage with them - treating AI as a technology project to be managed by the CTO and reported on quarterly - is no longer a viable option.

C-suite executives should consider three immediate priorities:

1) Make the organizational redesign explicit. AI transformation is a leadership challenge, not a technology project. Identify an executive sponsor with real authority, set clear value targets with measurable KPIs, and build the adoption engine that translates pilots into enterprise-wide capability.

2) Stop running more pilots. Assess honestly which of the four failure modes is limiting your organization. The answer will almost certainly involve data quality, operating model design, and culture - not the AI technology itself.

3) Invest in foundations, not just applications. The temptation is to fund visible AI use cases. The discipline is to invest in the underlying data infrastructure, platform, and change management capabilities without which use cases deliver nothing at scale.

The question is no longer whether AI will transform business. It will. The question is whether your organization will be among the 5% that capture the value, or the 95% that unwittingly fund their competitors’ advantage. Unlike the emperor’s clothes, the technology is real this time. The challenge is learning how to wear it.

Jeffrey D. Sachs is a world-renowned economics professor, bestselling author, innovative educator, and global leader in sustainable development. He is University Professor at Columbia University and Director of its Center for Sustainable Development. He is President of the UN Sustainable Development Solutions Network and has advised governments, heads of state, and international institutions on economic development for four decades. His books include The End of Poverty, The Price of Civilization, and The Age of Sustainable Development.

C-Suite: The postwar trading system is fracturing – tariffs, industrial policy, export controls – on a scale we haven’t seen in decades. What is driving this, and what should business leaders understand about it that most don’t?

The postwar trading system was a genuine success story. It produced decades of growth, enabled poorer regions to develop, diffused technology globally, and did exactly what Adam Smith described in 1776: a larger market allows for specialization and mutual benefit. The problem is that this history gets badly misread the moment you adopt a zero-sum mindset, where any gain by China is automatically a loss for America. On that logic, China’s development becomes a threat rather than a shared achievement and letting China into the WTO becomes the greatest mistake America ever made. I think that is a fundamental misunderstanding, and it is driving policy off a cliff.

There are two specific conceptual mistakes at the core of current U.S. trade policy. The first is that China took our jobs and we’re going to get them back. I was recently in a solar module plant outside Shanghai – several football fields in size, one of the top producers of panels in the world – and there were perhaps twenty people in the entire facility. Every machine was robotic and AI-driven. You cannot bring jobs back that no longer exist. Manufacturing employment in the U.S. actually fell by 100,000 jobs between January 2025 and January 2026. That trend will continue, because manufacturing is becoming overwhelmingly a robotics and AI-driven process across virtually every industry.

The second mistake is the belief that trade deficits reflect unfairness by China or others. This is something I address on the first day of my international monetary economics class. A trade deficit reflects the fact that you are spending more than you are producing, for whatever reason. In the American case, we have a giant national credit card called the federal government, which borrows roughly 7% of GDP right now. We spend a lot of money that we borrow from abroad. This has been going on for forty years, since Ronald Reagan initiated two generations of tax cutting. We’re now hemorrhaging public debt, and the trade deficit is a consequence of that, not of Chinese unfairness.

The trading system worked. We are now in the process of destroying it. What I hear from the people driving U.S. trade policy – the Lutnicks and Navarros of this world – would not pass for a first-year student in a first-year trade class. None of it holds any water.

C-Suite: How should boards be thinking about political risk in the context of U.S.-China relations becoming increasingly contentious and with some people invoking a Thucydides Trap (the idea that a rising power and an established one tend toward conflict)?

The clearest explanation of the U.S.-China situation that I know is a paper written in March 2015 by Robert Blackwill and Ashley Tellis for the Council on Foreign Relations, titled “A Grand Strategy for the United States Toward China.” I don’t agree with any of it, but it is admirably clear, and I think it is an explication of actual American statecraft rather than just a thought piece.

The paper’s logic is explicit: America’s grand strategy is primacy and China’s rise is a threat to primacy. Therefore, China’s continued rise is no longer in America’s interest. It then lists what to do, and the list is exactly what has been done; export restrictions on technology, trade blocs that exclude China, military build-up along China’s rimlands, and so forth. Nine or ten headline strategies, all of which have been pursued in the last decade. To my mind, none of them works. None actually contains China or advances American interests. But they do break apart the trading system and create significant problems for the United States going forward.

The two economies were deeply interpenetrated until recently. We have supply chains that depend on China, and we have markets in China, and they are being broken apart.

C-Suite: You described a solar module plant outside Shanghai. Green technology more broadly, where does that fit into the competitive picture for business leaders?

Climate change is not a hoax. It is something very serious, and it is getting worse at a dramatic and accelerating rate. Whoever dominates green technology in the future is going to, at a business level, make a lot of money, and at a national level, make a successful economy.

The United States has largely abandoned that sphere. China, I think, will be at the center of green technology for the next twenty to twenty-five years, given where things stand right now. This is very regrettable, and it is also a massive strategic mistake. On electric vehicles specifically, unless I am misreading something, we are absolutely surrendering that industry to China. Trump is not merely aggravating this. He may be putting a stake through the heart of the American automotive sector outside the protected domestic market. And we know that kind of protected market doesn’t last long.

For a C-suite executive, the first question should always be: what is the real future market or trend that is relevant to my business? And the answer, for almost anyone with exposure to energy, manufacturing, or transportation, is that green technology is one of the defining competitive battlegrounds of the next two decades. Simply denying this reality is deeply counterproductive.

C-Suite: You have been a long-standing critic of the IMF and the World Bank, and of the U.S. role in the international financial system. What do you see as the future of that system and what should CFOs be doing about it now?

Let me explain my critique from the ground up. At a core level, financial markets are crucial for a functioning economy, but they are intrinsically unstable. They rely overwhelmingly on expectations, which are subject to all sorts of influences and self-fulfilling prophecies. History is pockmarked by panics, manias, and crazes. This is well understood in financial history and has occasionally been rewarded with Nobel Prizes.

The two greatest accomplishments in modern monetary policy came in 1933 and 1934, in the depths of the Depression: the Federal Reserve finally understood that it was the lender of last resort to the banking system, and the introduction of federal deposit insurance. Those two changes put an end to the kind of commercial banking failures that had plagued the U.S. roughly every twenty years: 1873, 1893, 1907, 1933. What looked like an intrinsic feature of capitalism turned out to be a defect that could be corrected by clear and relatively straightforward policies.

When that lender-of-last-resort function fails, or is withheld, the consequences are catastrophic, as 2008 showed. The disaster of September 15th occurred because the Treasury Secretary forced Lehman Brothers into bankruptcy, almost to prove a point to Wall Street. He could have arranged a Barclays acquisition and avoided a multi-trillion dollar calamity. Instead, we had a collapse that put the world economy into a tailspin for several years. That was a pure policy mistake, and it is exactly the kind of mistake that a properly functioning international lender of last resort is supposed to prevent.

C-Suite: And where does the U.S. role in all this come in?

My critique of the current system is that the United States is misusing the dollar by weaponizing it. Twenty years ago, the U.S. began confiscating countries’ reserves, blocking countries from using SWIFT, and deploying other such measures as instruments of foreign policy. I believe these two things must be kept completely separate. Foreign policy is one thing; monetary policy is another. When foreign policy people meddle in the financial system, they destroy it and they are destroying the role of the dollar very quickly right now.

My critique of the IMF is that it is not the international lender of last resort that it should be. If financial markets are intrinsically unstable, you need a lender of last resort, just as the Fed is within the domestic system. Instead, the IMF functions more like a mortician. The country arrives dead after the crisis has already occurred, the debt is already in suspension, and the IMF dresses up the corpse. It takes three or four years for the zombie to come back to life. The IMF does not act proactively; it is not permitted to. It does not lend freely and quickly in a crisis mode to prevent the panic. It works on the debt workout once an insolvency event has happened.

The World Bank’s situation is different. My critique there is simply that it is too small. It lends $50 to $100 billion a year in a world economy of over $100 trillion. It has a prestigious address and a big name, but it is a tiny player. One reason it remains small is that if it were larger, China would get a bigger vote, and the United States prefers that it stay small with China’s influence limited.

C-Suite: Do you see any of that changing in the near future?

Probably not, because the geopolitical issue is not being wisely handled. What the United States should be doing is making the world safe for multipolarity. I started saying this about thirty years ago: we would have a multipolar world, and a far-sighted United States would help shape that world in ways that serve our long-term interests. Instead, we have pursued a strategy of preserving primacy, which puts us into conflict with the other major powers, Russia and China. That, I think, is the root of most of the problems we face right now.

I had some hope that Trump rather understood this was a multipolar world. Marco Rubio even said as much in one of his first statements as Secretary of State. But Trump said a couple of days ago that America’s goal is to remain the undisputed powerhouse of the world. That turned out to be the real policy. And that is very hard to sustain when you are 4% of the world’s population, a lot of clever people are everywhere else, and none of them are particularly interested in following American demands. The goal America has set for itself is unachievable, and the mere act of pursuing it is therefore extremely dangerous, because it is delusional.

C-Suite: On the dollar specifically, how significant is the de-dollarization risk on a five-to-ten-year horizon, and what does that mean for a CFO or treasurer?

Right now, the dollar is the currency of invoicing and settlement for roughly 60% of international transactions; the renminbi is around 5%. Ten years from now, I would expect the renminbi to be the currency of settlement for at least 20% of international transactions, and the dollar to be below 50%. We will definitely be in at least a two-currency system. You could imagine it being more. The Euro could become a more significant international currency if Europe and the U.S. have more separation, which seems increasingly likely given the current trajectory.

Twenty years from now, there will probably be an African currency covering most of the continent, a convertible rupee, a convertible renminbi, and the dollar will not dominate by any means. It may account for 30% of international trade, but it will not stand out as the world’s currency. We will not necessarily go the way of the pound sterling; it took two world wars and the end of the British Empire to break sterling, and God forbid anything remotely like that happens.

For a treasurer today, bank accounts denominated in renminbi, probably in rupees, and even in rubles, are all going to play a much bigger role in the future. That is something to be building into your financial planning now, not in ten years.

C-Suite: Given everything we’ve discussed about technology and economic development, what is your overall assessment of the potential impact of AI?

I am, in general, a technophile, and I am a believer that AI is very real, extraordinarily powerful, and not hyped. I would not have believed, ten years ago, that you could train a trillion-parameter model and have it available for a substantive intellectual discussion. As a daily and hourly user of AI for the work I do, I can say I am quite impressed. It reads journals faster than I do, it summarizes things extremely well, and for someone who works with data and information intensively, it is a huge advance.

In Chinese factories today, AI is already deeply embedded at every stage of production. In one plant I visited outside Shanghai, every machine had an AI role: testing whether wiring had been placed correctly, whether leads were properly set, whether electrolytes were balanced – all without a person anywhere in sight. This is manufacturing in China right now.

C-Suite: How does that translate to the labor market?

I also think AI will have profound and difficult effects on the labor market. Over the last two hundred years, technology has basically eliminated more jobs than it has created, and on the whole, that has been good. Our economy, at nearly $90,000 per capita, operates with adults putting in an average of three hours and fifteen minutes of work per day, according to U.S. government time-use surveys. What used to be twelve-to-fourteen-hour days of physical labor has been replaced, not by other jobs, but by leisure, study, retirement, and weekends. If you simply allow AI to do its job without any policy response, however, you will produce an underclass that is profoundly large. The approach, in one way or another, has to be to socialize a significant portion of consumption – through education, healthcare, public services – so that people’s living standards are not tied entirely to their individual position in the labor market. The United States does this much worse than Europe, and we have no coherent plan for what AI is going to do next, which will be a faster and larger effect than robotics was on the assembly line over the last thirty years.

C-Suite: What about for developing countries? Do you think AI will narrow or widen the gaps?

On the whole, I think it will narrow the gaps, though it does one thing that dramatically changes the development picture: it eliminates the labor-intensive manufacturing pathway that drove the great successes of Asia over the last fifty years. China, and the Asian Tigers before, all moved up the technology ladder from assembling electronics and cutting apparel to more advanced manufacturing. That pathway is gone. There are no jobs left in labor-intensive manufacturing; they are being automated and quickly.

But the advantages of AI for development on the other side are enormous. Education can be completely revolutionized. Healthcare can be completely revolutionized. Payment systems, credit systems, farm management, public service delivery: everything can be transformed, and I am seeing this happen in very poor settings. In India, you can go to the most remote rural village and every vegetable vendor has a QR code for online payment. I am involved in projects putting AI into the hands of high-school-educated health workers and nutrition support workers in villages, and it works extremely well.

The fundamental redesign of development strategy is now at hand. An African country is no longer going to sell unskilled labor. It is going to sell strategic minerals, downstream battery supply chains, commodity-based industrialization in metallurgy or specialty steels, agro-industry, tourism, the creative economy, online services. But it is going to have to be skilled. And that creates a very different set of priorities. I am working on exactly this with a number of governments and with the African Union right now. On the whole, this is a huge plus, because suddenly you have a very information-rich environment in a low-income setting, which was not the case before.

C-Suite: The U.S. has essentially dismantled its development aid programs. What is the realistic trajectory for Sub-Saharan Africa and other developing regions, and what role, if any, does aid play going forward?

I spent the first twenty or twenty-five years of my career promoting these programs, and I am proud of some of it. I believe I was the progenitor of the Global Fund to Fight AIDS, TB, and Malaria, and that has saved millions of lives and proved the point I made at the time; that there are low-cost interventions that could have a huge benefit and that were simply not getting done otherwise. It worked.

I always thought a little generosity could go a long way, and I liked the idea that the rich world should give 1% of its income to the poor. It turned out to be impossible. The United States came closest to that target in the Marshall Plan era, approaching 1% of GDP, before falling to around half a percent through the 1950s and declining from there. Aid collapsed further when the Soviet Union ended, because a lot of it had been motivated by competing for hearts and minds with the Soviet threat. We reached about 0.1% of GDP, and now we have eliminated development aid altogether.

Since I do not like pounding my head against a wall, I have largely stopped dealing with aid as such over the last ten years – not because it was wrong, but because it was a losing approach. I was not making headway. So now I spend most of my time trying to make the financial system work better for poor countries. Most of what is needed in development can be done through market finance, just not five-year euro bonds. Development is a twenty-five-year process, not a five-year process. If you borrow at five-year maturity for a twenty-five-year investment and you are a developing country, you are going to get into a debt crisis before your investment pays off. The case for maturity matching in development finance is fundamental and has never been seriously addressed.

As for aid today, it is not even a topic of polite conversation in Washington. It is simply not on the table. The task now is to build development finance mechanisms that do not depend on political generosity that never reliably materializes.

C-Suite: If you had to name one thing that most C-suite leaders are systematically getting wrong about the world right now, what would it be?

I want to be fair to business leaders here. In general, they are smart, practical people trying to make their businesses work. Where I see the real delusions are in Washington, not in the boardroom. Business leaders are trying to figure out what to do in a world they did not make and cannot fully control.

But what they should know is this: there is a big world out there, and it is a very sophisticated world. There are places with excellent technology and highly capable people everywhere you look, including places that American foreign policy has caricatured. The world doesn’t go away because we say so. It does not follow U.S. demands simply because we demand it.

The United States should continue to try to be a competitive, active, outward-looking, and optimistic part of the world. That is our best hope and our heritage. The great American strength has been our capacity to draw talent from all over the world, and to understand that science and technology are at the base of our long-term strength. Both of those are currently under self-attack; through the treatment of our universities, through the signals we are sending to foreign students and researchers who are now genuinely afraid to cross the U.S. border.

I can tell you that all of my foreign students are afraid right now. Every one of them, when they cross the border, does not know whether they will be coming back, whether they will be pulled aside for questioning at the airport, whether their phones will be confiscated, whether their social media will be read. A lot of students who would normally have come to the United States are now looking to study elsewhere. These are not mistakes of C-suite executives. But they are things that C-suite executives should know, and should factor into how they think about talent, innovation, and the long-term vitality of the American economy.

We do best when we are optimistic, outward-looking participants in a big, diverse world. We do worse when we view that world with fear and try to close up. That is not merely a political observation, it is an economic one.

Welcome to the April issue of The Briefing Table. This month’s edition covers four forces that defined the past few weeks and that will likely shape the strategic environment through the rest of 2026: the Iran war and its consequences beyond the oil price, the Supreme Court’s landmark tariff ruling, a U.S. economy absorbing both shocks simultaneously, and an AI governance gap that is closing in on its first major regulatory deadlines.

1) The Iran War: Beyond the Oil Price

The most significant development of the past week is the collision of simultaneous signals that point in opposite directions and remained unresolved after last night’s presidential address. Thousands of additional U.S. troops have arrived in the region, reportedly positioned for a potential seizure of Kharg Island or Iranian nuclear stockpiles. The administration has explicitly threatened to withdraw from NATO if European allies do not take a greater share of the burden in protecting Hormuz, which suggests a willingness to use the alliance itself as a bargaining chip. The economic consequences of the war were barely mentioned. Markets responded with oil prices up and futures down. Whether all this represents a strategy or the absence of one is genuinely unclear. What is clear is that resolution, when it comes, is likely to be abrupt, and, unlikely to restore the conditions that existed before the war began. (Readers looking for the full conflict scenario framework will find it in our recent special briefing; this section focuses on what has changed and on two exposure dimensions receiving insufficient attention.)

The first underappreciated exposure is competitive rather than operational. This shock is not landing symmetrically around the world. China holds crude reserves estimated at roughly 120 days of imports, its domestic pricing mechanisms insulate manufacturers from immediate pass-through inflation, and its twenty-year electrification bet is paying off precisely when its Western rivals are most exposed. Chinese manufacturers may actually gain a cost advantage in energy-intensive sectors as this shock persists, echoing what happened after the Russia-Ukraine war in 2022. McKinsey’s March 2026 Global Survey confirms the asymmetry in executive sentiment: respondents in Asia-Pacific, Greater China, and India lean more positive than negative about near-term conditions, while those in Europe and North America are the most likely to report worsening conditions and the least likely to expect improvement. The deeper irony: with China controlling more than 80% of global solar, wind turbine, and battery production capacity, the supply chain for the energy transition this conflict is accelerating runs predominantly through Beijing. For executives in energy-intensive industries, this is a present-tense competitiveness question, not a future-tense strategic concern.

The second is the semiconductor and AI infrastructure exposure. Qatar’s Ras Laffan shutdown has closed off a major source of helium, essential for chip fabrication, fiber optics, and MRI machines. The Gulf region supplies roughly half of global sulfur exports, the feedstock for the high-purity sulfuric acid required to manufacture clean silicon wafers. Iranian drone strikes have already damaged two AWS data centers in the UAE and a facility in Bahrain. Gulf sovereign wealth funds, which have been among the largest investors in AI infrastructure globally, are redirecting capital toward domestic reconstruction. The conflict is simultaneously disrupting the physical inputs, the cloud infrastructure, and the investment capital underpinning most companies’ AI buildout assumptions. Few strategy teams have modeled all three.

Bottom Line: Most energy cost exposure has now been identified. The less-modeled risks are China gaining ground in energy-intensive industries while Western rivals absorb the shock and supply chain disruption running through semiconductor inputs and AI infrastructure. Both warrant immediate audit. On scenario planning: do not treat a sudden ceasefire as a return to normal. Iran has demonstrated it can close the Strait; that capability does not disappear with a peace agreement. Real shipping and oil market disruptions would persist for weeks after any ceasefire, Iranian leverage over the waterway is now an established fact rather than a theoretical risk, and the regional power balance has shifted in ways that will outlast the conflict. The status quo ante is gone. Plan for a new baseline, not a restoration.

2) The IEEPA Ruling: The Tariff Wars Enter a New Phase

On February 20th, the Supreme Court ruled 6 to 3 that IEEPA does not authorize the President to impose tariffs. Chief Justice Roberts held that tariff authority is “very clearly a branch of the taxing power” reserved for Congress. The decision invalidated the reciprocal tariffs and most of the tariff architecture built since Liberation Day. As we previewed in December, the ruling has created nearly as much new uncertainty as it resolved.

The administration moved within hours. Section 122 of the Trade Act of 1974 now imposes a 10% global tariff pushed toward the 15% ceiling, expiring July 24th unless Congress extends acts to extend the measure. New Section 301 investigations were launched targeting 16 economies, including China, the EU, Japan, Mexico, and Vietnam, for structural excess capacity. An additional 60 investigations were launched for failures to enforce forced-labor bans. Section 232 tariffs on steel, aluminum, and autos remain fully intact. As a result, the effective tariff rate, at approximately 10.5%, remains at its highest level since 1943. The paradox of the ruling is that it has replaced a fast, legally fragile instrument with slower ones that are harder to challenge and longer-lasting in their effects. IEEPA tariffs could be imposed overnight and litigated immediately. Section 301 findings take 12 to 18 months to reach conclusions which are far more durable once they do.

Two pressure points deserve attention. Penn Wharton projects up to $175 billion in potential IEEPA refunds, but the Court left the mechanism to the Court of International Trade, which is managing nearly 2,000 pending cases; CBP cannot begin processing until mid-April at the earliest. Large importers are sitting on a potential windfall wrapped in procedural uncertainty, arriving in the middle of an energy crisis. Separately, the July 1st USMCA review deadline, overshadowed by the IEEPA drama, may prove more consequential for North American supply chains than the ruling itself. Canada has recently signaled a willingness to explore a North American “fortress” approach to energy and raw materials, but that posture has not softened Washington’s negotiation position. The realistic outcomes range from managed renewal with modified terms, to collapse into separate bilateral deals, to large unilateral actions against Canada, which remains more exposed than Mexico given its energy and resource dependencies. One further signal worth registering: McKinsey’s March 2026 Global Survey finds that geopolitical instability has now overtaken trade policy as the most-cited threat to company growth for the first time since March 2025. The legal and trade architecture remains unsettled, but executive attention has already moved on.

Bottom Line: Three simultaneous actions: file or preserve IEEPA refund claims before procedural windows close; map your supply base against the 16 Section 301 investigation targets; and begin USMCA scenario planning before July 1st forces a reactive posture. The tariff environment has not stabilized. It has restructured around a less predictable legal architecture, and this restructuring is arriving into an economy simultaneously absorbing an oil shock and a monetary policy dilemma.

3) The U.S. Economy: Stagflation Lite Is No Longer a Forecast

In November, we identified two Gray Rhinos preparing to charge: tariff pass-through to consumers and the risk of an AI investment bubble. The Iran war now adds a third. What unites all three is a common structure: their costs were largely deferred in 2025 through inventory pre-stocking, energy price normalization, and AI investment not yet faced with a demand test. They are now arriving simultaneously, however, and without the buffers that cushioned last year’s shocks.

The headline numbers still look passable: GDP growth projected around 2%, unemployment at 4.4%, and markets volatile but intact. The structure beneath those numbers is less reassuring. The wealthiest 10% of households now generate nearly half of all consumer spending, with Deloitte estimating 20-25% of that driven by the wealth effect from rising asset prices. That support disappears quickly in a sharp equity correction. Bank of America Institute data shows younger Gen Z and Millennials consumers, who had finally begun outspending older cohorts on the back of easing rents and strong wage growth, have disproportionately high gasoline spending relative to their discretionary budgets. A sustained fuel shock will reverse recent momentum in retail, restaurants, and consumer electronics precisely in the demographics driving it.

McKinsey’s March 2026 Global Survey on Economic Conditions captures how quickly the picture changed. Executives surveyed before February 28th were as optimistic as they had been in December, the most upbeat quarter of 2025. From February 28th onward, the share indicating global conditions had worsened nearly doubled, and forward expectations flipped from net positive to net negative within 72 hours. The share citing supply chain disruptions as a top risk doubled in the same window. This is not a gradual deterioration. It is the kind of sentiment shift that arrives faster than quarterly planning cycles can accommodate, which is why the contingency planning argument in this issue is not about managing disruption but about matching its speed. There is, however, a complicating signal: at the company level, expectations remain primarily optimistic. Just over half of private sector respondents still expect demand for their products and services to increase in the next six months, and about six in ten expect profits to grow. That gap between a sharply deteriorating macro-outlook and continued company-level optimism, is a pattern worth watching. It tends to resolve in one direction only, and rarely does the macro picture turn out to be wrong.

The monetary policy picture has deteriorated materially. The Fed held rates steady on March 18th and penciled in at most one cut for 2026, down from the two cuts markets had been pricing before the war. Several analysts suggest no cuts will be delivered this year. The ECB, facing a more severe energy exposure, has already postponed planned reductions and warned of stagflation risk in Germany and Italy. The Fed cannot address both sides of this dilemma at once: holding rates to contain inflation risks tipping a softening labor market into something worse, while cutting to support growth risks entrenching energy-driven price pressures. Any capital allocation plan built on an assumption of two or more rate cuts in 2026 needs to be revisited. Chairman Powell’s term expires in May. As we analyzed last July, a successor perceived as politically accommodative could push long-term bond yields higher even as short-term rates fall, precisely the wrong environment for capital-intensive businesses.

Bottom Line: Goldman Sachs has raised its 12-month U.S. recession probability to 30%; Moody’s Analytics sits at 42%. Review capital expenditure plans and debt covenants. Build variable cost flexibility into the operating model. But the most important action may be the simplest: put your macro assumptions and your company forecast in the same room and ask whether they are consistent. McKinsey’s survey suggests most executives will find that they are not. That gap does not stay open. It closes and it is rarely the macro picture that moves.

4) Agentic AI: The Governance Gap Is Now a Board-Level Liability

In December, we cautioned against the tendency to go “all-in” on emerging technologies before the enabling infrastructure is in place, a pattern repeated across EVs, autonomous vehicles, fuel cells, and telematics. That warning applies with even greater urgency to agentic AI, with one important difference: the automotive industry’s overcommitments primarily affected capital budgets. AI governance failures will affect customers, regulators, and reputations simultaneously, and the regulatory deadlines are no longer abstract.

The shift happening in 2026 is not simply more AI. Generative AI assistants merely make recommendations. Agentic systems act on them, initiating transactions, sending communications, modifying data, and orchestrating workflows across enterprise systems without human review at each step. Only 21% of enterprise leaders report having a mature governance model for autonomous agents. Meanwhile, 65% of AI tools inside enterprises operate without IT oversight, adding an average of $670,000 to the cost of a data breach. The AI running inside your organization today is almost certainly not fully visible to the people responsible for managing its risks.

The governance gap persists not because executives are unaware of it but because the standard response - approving AI tools through procurement and IT review - is structurally mismatched to the actual risk. Approving a tool is not the same as governing its execution. With generative AI assistants, that distinction was manageable: the human read the output and decided what to do with it. With agentic systems, the human who authorized the agent is typically nowhere near the workflow when the agent acts. The accountability gap is not a process failure. It is an architectural one.

Three regulatory deadlines are now inside any responsible planning horizon. The EU AI Act reaches full general application August 2nd. Colorado’s AI Act takes effect June 30, with specific obligations around algorithmic discrimination. California’s generative AI transparency requirements are already active. The FTC’s “Operation AI Comply” in 2025 established that regulators expect documented controls and technical safeguards, not aspirational ethics statements. The governance question boards should be asking is not whether to govern AI but at what level. Tool-level governance, meaning the approval of AI systems, misses the risk. The risk lies in what agents do, not what they are, which means governance must be built into the workflows agents operate within, with clear accountability for every action they can take.

Bottom Line: The governance gap in enterprise AI today is where corporate cybersecurity governance was in 2003: widely acknowledged, but rarely addressed with appropriate seriousness, until high-profile failures made inaction untenable. The firms that built the infrastructure before the breaches gained lasting competitive and reputational advantages.

Key Take-Aways

• Model the full exposure, not just oil prices. Map every input that transits the Strait of Hormuz or originates in the Gulf, including indirect dependencies like helium, sulfur, and industrial gases. Most companies have done this for crude oil. Few have done it for the second- and third-order inputs that are quietly closing semiconductor and AI supply chains.

• The tariff regime has restructured, not stabilized. File IEEPA refund claims promptly, map your supplier base against the 16 Section 301 targets, and begin USMCA planning before the July 1st deadline. The effective tariff rate remains near an 83-year high, and the administration has demonstrated it will find new instruments whenever old ones are removed.

• Your macro assumptions and your company forecast are probably inconsistent. McKinsey’s March survey finds executives remain primarily optimistic about their own firms’ demand and profits even as their macro outlook has deteriorated sharply. That gap tends to close in one direction. Audit your company-level plan against the macro picture explicitly, not as a separate exercise but in the same room, with the same set of assumptions, at the same time.

• Govern AI at the workflow level, not the tool level. The risk is in what agents do, not what they are. Commission a governance review that covers agentic systems specifically, maps accountability to individual agent actions, and meets the EU AI Act, Colorado, and FTC standards. The August deadline is the forcing function.

• Build contingency plans in both directions. A rapid negotiated off-ramp is as plausible as further escalation, and it could arrive with virtually no warning, as last Monday’s 14% oil price swing demonstrated in both directions inside a single trading session. Scenario planning should be explicit about both endpoints and the speed at which transitions can occur. Companies that prepare only for continued disruption will be as wrong-footed by a sudden normalization as those that failed to prepare for the disruption itself.

The markets initially seemed to shrug this off as a short, decisive operation with a defined endpoint. That framing was wrong, and the longer executives plan around it, the more costly the mistake. Three questions will determine what comes next: How is this conflict likely to evolve, given the diverging interests and decision-making constraints of the key players? What are the most plausible scenarios over the coming weeks and months? And, most importantly, what should U.S. companies actually do?

The answers run contrary to the conventional wisdom. The disruption is worse than markets currently reflect. The path to resolution is narrower than it appears. And the business implications extend well beyond the energy sector into areas, including semiconductors, AI infrastructure, and monetary policy, that few strategy and risk management teams have begun to model.

Three Players, Three Constraint Sets

The trajectory of this conflict is best understood not as a coherent campaign with a defined endpoint, but as the product of three actors whose interests only partially overlap and whose room to maneuver is more constrained than their public postures suggest.

1. The United States: Military Success, Strategic Uncertainty

Militarily, the U.S. has clearly had the better of the early exchanges. Iran’s senior leadership has been decapitated, its missile launchers have been destroyed, and the U.S. has achieved air supremacy with minimal American losses. What has proven far more elusive is a strategic objective that is both achievable and politically sustainable.

The closure of the Strait of Hormuz was an entirely predictable Iranian response to a major military campaign. Iranian officials had telegraphed it for years, and energy analysts had long priced it as an obvious contingency. Whether or not it was adequately planned for, the U.S. now faces a situation in which the most painful consequence of the conflict, a global energy crisis landing hardest on American consumers, was widely foreseen.

Recent U.S. moves point in two directions simultaneously. The un-sanctioning of Iranian oil exports, functionally the reversal of the first-term maximum pressure posture, signals that off-ramps are being actively explored. The simultaneous deployment of U.S. paratroopers and a Marine expeditionary unit to the region signals that escalatory options are being kept open. The tension between those two signals is the defining feature of the current moment.

2. Israel: Different War, Different Objectives

Israel entered this conflict with its own logic and its own definition of success: the permanent degradation of Iranian nuclear capability. Its strikes on Iranian gas facilities, conducted according to Israeli officials with U.S. awareness, have generated visible friction with Washington even while advancing Israeli objectives. The divergence matters for business scenario planning: Israel’s interests in a swift resolution are considerably more limited than America’s. A prolonged conflict that keeps Iran militarily degraded and its nuclear program set back by years is not, from Tel Aviv’s perspective, an unfavorable outcome, regardless of the cost to the global economy. Any negotiated endgame will have to resolve this structural misalignment between the two allies, and there is no obvious mechanism for doing so, at least not quickly.

3. Iran: Severe Losses, Escalatory Ceiling Not Yet Reached

Iran has sustained severe military losses and has seen much of its conventional deterrent capacity destroyed. And yet it has not come close to deploying its full asymmetric arsenal.

The Strait of Hormuz closure, severe as it has been, is not Iran’s ceiling. Iran retains an extensive sea mine capability that has barely been used, a fast-attack boat fleet capable of threatening U.S. naval vessels, and the ability to expand attacks to Gulf desalinization plants and other civilian critical infrastructure that sustains human life across the region. The officials now making these decisions are, by definition, those who survived a targeted decapitation campaign. Their incentives are not necessarily aligned with de-escalation.

The market, to the extent it is pricing the current disruption as the likely endpoint of Iranian escalation, is almost certainly wrong. Companies stress-testing their exposure should model a scenario in which the current level of disruption is not the floor but the baseline, with meaningful probability of further deterioration.

Three Scenarios and Why None Is Reassuring

Based on the constraints above, three broad scenarios are plausible.

Scenario 1: Declare Victory and Wrap It Up

Back-channel negotiations produce a ceasefire framework. The U.S. declares victory based on military results achieved, while Iran halts Strait disruptions in exchange for sanctions relief and security guarantees. The Strait reopens partially within weeks, fully within months.

The preconditions are currently absent. There is no agreed U.S. definition of victory significant Israeli resistance to any outcome that leaves Iranian nuclear infrastructure intact, and there may not even be a functioning Iranian interlocutor with authority to make binding commitments. The scenario is nonetheless worth modeling and preparing for, because it could materialize abruptly if domestic political pressure intensifies. Companies that have not prepared for a rapid normalization will be as wrong-footed as those that did not prepare for the disruption itself.

Scenario 2: Escalate to De-escalate, the Dangerous Middle

This is the current trajectory. Periodic U.S. escalation, strikes on new Iranian targets, is intended to signal resolve and create pressure for negotiation. In theory, it produces an off-ramp. In practice, it has so far produced the opposite: Iranian counter-escalation and a visible split between the U.S. and Israel.

The deeper problem is credibility. The rational Iranian inference from recent U.S. moves, specifically the disavowal of certain strikes shortly after they occurred and the reversal on oil sanctions, is that Washington is more sensitive to energy prices than it is committed to continued escalation. An escalate-to-de-escalate strategy is particularly dangerous when the adversary has correctly assessed that the escalatory threat is not fully credible.

Scenario 3: Go Big, Force the Strait Open

The third option involves committing to a decisive military campaign: forcing the Strait open by naval and ground operation, potentially including the seizure of Iran’s primary oil export terminal at Kharg Island. Marines and paratroopers being deployed to the region are the relevant capability; boots on the ground have not been taken off the table.

The appeal of this option is real and should not be dismissed: it would, in theory, resolve the energy crisis by removing its source. Its problems are equally real. The Strait was open before the war started; making its reopening the war’s central objective means the U.S. is now fighting to undo the most predictable consequence of a war it chose to start. U.S. forces have already struck more than 90 targets on Kharg Island while deliberately preserving the oil infrastructure there, but holding the island against continuous Iranian attack from the mainland is a different proposition entirely: an indefinite occupation of a contested asset with no clear exit, subject to the full weight of Iranian countermeasures not yet deployed.

Most Likely Path: Extended Disruption, Abrupt Resolution

The near-term base case is Scenario 2, continued escalation and stalemate, with a non-trivial probability of migration toward either Scenario 1 or Scenario 3 depending on two variables: the trajectory of U.S. gasoline prices and the administration’s read of Iranian credibility. Watch both as leading indicators.

The synchronized global demand data published this week provides the first hard evidence that the economic damage is no longer confined to the energy sector. Every composite PMI index released on Tuesday, covering the U.S., Eurozone, UK, Japan, India, and Australia, came in below expectations. The American reading showed business activity expanding at its slowest pace in nearly a year. A gauge of prices paid for inputs jumped to the highest since May. What began as a supply shock is now registering as a demand shock as well. Goldman Sachs has raised its 12-month U.S. recession probability to 30% as a result of the oil price surge, and projects unemployment rising to 4.6% by year-end.

Four things can be stated with reasonable confidence:

• The Strait of Hormuz will not reopen meaningfully in the next 30 to 60 days under any scenario short of a comprehensive ceasefire. Strategic petroleum reserve releases, Jones Act waivers, and rerouting around the Cape of Good Hope provide marginal relief; they do not address the core problem: there is no alternative route capable of moving the volume of oil and gas currently stranded in the Middle East.

• Qatar’s Ras Laffan LNG facility is offline for the duration of active hostilities. The global LNG market is structurally altered for the medium term. European and Asian consumers are not returning to pre-war supply conditions on any near-term timeline.

• The current level of Iranian escalation is not the ceiling. The risk of further deterioration, expanded mine warfare in the Strait, attacks on Gulf desalinization plants, broader civilian infrastructure targeting, is real and underpriced in most business planning models.

• Resolution, when it comes, is likely to be abrupt. A single presidential social media post on Monday sent oil down 14% in minutes, then Iran’s denial of any talks sent it back up. Companies need contingency plans in both directions, and they need to assume they will have very little warning when the direction changes.

Implications for U.S. Companies

The Exposure You’ve Modeled, and the Exposure You Haven’t

The direct energy cost impact is the most visible and has received the most attention. Gasoline approaching $4 a gallon nationally, up more than a dollar since the conflict began, elevated industrial energy costs, compressed margins in energy-intensive operations: executive teams have been running these numbers. Two things are worth adding to that analysis.

First, Bank of America Institute data published this week shows that Gen Z and Millennial consumers, who had finally begun outspending older cohorts buoyed by easing rents and strong wage growth, have disproportionately high gasoline spending relative to their discretionary budgets. A sustained fuel shock is likely to reverse recent momentum in retail, restaurants, and consumer electronics spending precisely in the demographics that had been driving it. Consumer-facing companies should be revising their near-term demand models now.

Second, the supply chain disruptions extend into inputs few companies had thought to track. Qatar is one of the world’s largest suppliers of helium, a byproduct of natural gas extraction essential for semiconductor manufacturing, fiber optics, and MRI machines. The Gulf region supplies approximately half of global sulfur exports, which produce the high-purity sulfuric acid required to manufacture clean silicon wafers. The same conflict raising gasoline prices is quietly creating a serious bottleneck in semiconductor manufacturing that will ripple through the technology supply chain for months. Companies with exposure to chips, which is to say virtually every company, should be auditing this now.

Third, executives with European operations or customers are facing a harder version of this shock than the U.S. is. European natural gas prices have nearly doubled since the conflict began. Chemical and steel manufacturers across the EU and UK have already imposed input cost surcharges of up to 30%, and analysts are using the word “deindustrialization” not as a long-term structural concern but as a near-term operational risk in Germany and Italy. Unlike the Russia-Ukraine shock of 2022, the tools Europe used then, rerouting LNG, substitution, demand destruction, are largely unavailable here: Qatari LNG is offline, and Cape of Good Hope rerouting adds cost and time but cannot replace stranded Gulf supply. Companies with European exposure should not be benchmarking this disruption against 2022. The structural situation is materially worse.

The Rate Environment Has Changed, Whether or Not Your Plans Have

The war has created the macroeconomic environment that central bankers specifically dread: inflation rising while growth weakens simultaneously. The Fed held rates steady on March 18 and penciled in at most one cut for 2026, down from the two cuts markets had been pricing before the war began. Several analysts now think no cuts will be delivered this year. The ECB, facing a more severe energy exposure, has already postponed its planned rate reductions and warned of stagflation risk in Germany and Italy.

The Fed cannot address both sides of this dilemma at once. Holding or raising rates to contain inflation risks tipping an already softening labor market into something worse; cutting to support growth risks entrenching energy-driven price pressures. This is precisely the type of shock that monetary policy is not designed to address. Any capital allocation plan built on an assumption of two or more rate cuts in 2026 needs to be revisited. Companies carrying floating-rate debt, considering leveraged acquisitions, or planning major capital expenditures on the basis of continued accommodative conditions are operating with a planning assumption that has become materially less reliable in the past four weeks.

There is an additional layer that belongs in the CFO’s conversation. A single presidential social media post on Monday moved the oil price 14% in minutes. Unusual trading activity in oil futures roughly 15 minutes before that post was published has drawn scrutiny from market analysts and regulators. Whether or not that investigation produces findings, the practical consequence is significant: when price-moving information reaches some market participants before it is public, conventional hedging programs based on publicly available signals lose much of their effectiveness. Treasury teams should be reviewing whether their existing instruments are still fit for purpose in an environment where policy announcements, not supply-and-demand fundamentals, are the dominant price driver.

The AI Buildout Has a Gulf Problem

Gulf sovereign wealth funds have been among the primary drivers of AI infrastructure investment globally, funding data centers, semiconductor fabs, and the broader technology buildout that underpins most companies’ medium-term productivity assumptions. These funds now face a fundamentally different set of priorities: rebuilding domestic energy infrastructure, managing food security (the Gulf imports billions in cereals and produce by sea, and hundreds of dry bulk carriers are currently avoiding the region), and managing the political consequences of a conflict they did not choose. The redirection of Gulf capital away from AI and technology investment is not a theoretical scenario; it is already underway.

There is a more immediate dimension as well. Iranian drone strikes have already damaged two AWS data centers in the UAE and a facility in Bahrain. The fact that the world’s largest cloud computing provider has had physical infrastructure struck in this conflict changes the risk profile for any company with significant workloads running through Gulf-based data centers and raises questions about digital infrastructure vulnerability that most business continuity plans have not confronted. Companies whose medium-term plans assume continued aggressive AI buildout should be pressure-testing that assumption against a scenario in which both the capital enabling it and the infrastructure supporting it have been simultaneously disrupted.

China Is Not Absorbing the Same Shock You Are

While U.S. and European companies absorb higher energy costs, Chinese manufacturers face a structurally different picture. China has made a sustained 20-year bet on electrification, holds crude reserves estimated at roughly 120 days of imports, and its domestic pricing mechanisms provide significant insulation from immediate pass-through inflation. Chinese manufacturers may actually gain a cost advantage relative to rivals in energy-intensive industries as this shock persists, echoing the dynamic seen after the Russia-Ukraine war in 2022, when energy shocks disproportionately weakened Western production compared to Chinese exporters.

The clean energy dimension compounds this asymmetry with China controlling more than 80% of global solar manufacturing, wind turbine, and battery production capacity. As the conflict accelerates the energy transition argument in boardrooms across the U.S. and Europe, the supply chain for that transition runs predominantly through China. Companies accelerating their own renewable energy investments in response to this shock will find that the path to energy independence runs, for now, through Chinese suppliers. For companies competing globally in energy-intensive sectors, this is a present-tense competitiveness question, not a future-tense strategic concern.

What Companies Should Actually Do

Three concrete actions are warranted now, regardless of how the conflict ultimately resolves:

• Audit the full supply chain exposure, not just energy costs. Map every input that transits the Strait of Hormuz or originates in the Gulf region, including indirect dependencies like helium, sulfur, and other industrial inputs. Most companies have done this for oil; few have done it for second- and third-order inputs. The companies that did this work after COVID will have an advantage; those that did not should start immediately.

• Stress-test capital allocation and financing assumptions. Any plan premised on two or more Fed rate cuts in 2026, continued AI infrastructure buildout, or stable Middle Eastern supply chains was built on assumptions that no longer hold. This means specific attention to floating-rate exposure, leveraged positions, and whether existing hedging instruments are still fit for purpose when policy signals, not market fundamentals, are setting the price.

• Build contingency plans in both directions. A rapid negotiated off-ramp is as plausible as further escalation, and it could arrive with virtually no warning. Companies that prepare only for continued disruption will be as wrong-footed by a sudden normalization as those that failed to prepare for the disruption itself. The scenario planning exercise should be explicit about both endpoints and the speed at which transitions can occur.

Conclusion

Four weeks into this war, the business implications are running well ahead of most companies’ strategic responses. The executives who will navigate this best are not those who wait for the conflict to resolve before adjusting their strategies. They are those who recognize that the disruption already underway, combined with the escalatory risk that has not yet materialized and a monetary policy environment that has shifted materially against them, represents a structural change in business conditions rather than a temporary shock.

The most important number to watch is not the oil price. It is the gap between what the market is pricing as Iran’s escalatory ceiling and what Iran has actually demonstrated it is willing and able to do. Right now, that gap is large. Executives who close it in their planning before markets do will be substantially better positioned than those who do not.

C-Suite: You’ve labeled today’s workforce “Generation Numb.” Why?

Cardoz: We think it explains what’s going on in the world now. The modern workforce is undergoing a fundamental shift. Global upheaval, economic instability, the after-effects of the pandemic, and digital saturation are shaping a workforce that is numb. They are increasingly cynical, stuck, longing for connection, and hunting for a renewed sense of identity at work. People are still showing up. They’re still doing their jobs. But they’re operating in survival mode.

C-Suite: What evidence do you see of this?

Cardoz: The signals are everywhere. Nearly 60% of workers say they’re overwhelmed by the pace of change. There’s been a 36% drop in willingness to support change. Twenty percent experience loneliness daily. Half are worried they can’t pay their bills. Those numbers matter because they sit underneath every transformation program leaders are trying to execute, shaping how change lands, how quickly it’s adopted, and whether discretionary effort ever materializes.

C-Suite: What’s driving this numbness?

Cardoz: People are navigating a polycrisis. Recession, war, climate anxiety, polarization, rising inequality, all at once. At the same time, digital adoption now outpaces human adaptation. Each new technology reaches mass use faster than the last. We’re still recovering from the pandemic and adapting to hybrid work. What does it mean to be connected to colleagues but never meet them? What does it mean to enter the workforce from the same bedroom where you wrote your college papers? And then you add AI, which can be the biggest boost to your career but could also take your job tomorrow. The pressures are cumulative and relentless.

Haywood: Our diagnosis was triggered by what we were seeing with clients. We deliver large programs for major organizations, and these issues were affecting success. We drew on more than 40 third-party reports and conducted proprietary research across U.S. employees in large organizations, testing this concept of “numbness” across age cohorts. Feeling overwhelmed isn’t new. But what we’re hearing is, “I’ve been doing this for ten years and now I’m numb.”

C-Suite: How is numbness different from burnout and why does that distinction matter to business leaders?

Haywood: Most of the rhetoric is about burnout or mental health crisis. That describes the extreme end of negative emotion. What we found instead was that 60% of people describe themselves as “okay” or “indifferent.” That’s fundamentally different from being burnt out. It’s a person who waits in the wings to be energized, if leadership can unlock them. The danger is that numbness looks like “okay.” It doesn’t trigger alarms. But it steadily erodes the extra effort transformation depends on. It’s not quiet quitting. It’s not rejection. It’s numbness against more demands coming daily. It shows up in employees ignoring initiatives or not really engaging with them.

Cardoz: For a C-suite executive, that creates a dangerous illusion. You can be in the middle of a transformation - launching initiatives, deploying content, tracking milestones - while your execution capacity is quietly shrinking beneath you. There’s dissonance between the executive vision and where your people actually are. It’s related to Maslow’s hierarchy of needs. It’s hard to get excited about customers when you’re worried about the price of bread.

C-Suite: So this becomes a strategy execution issue, not just an engagement issue?

Haywood: Absolutely. Companies are making major investments in transformation, particularly AI, but they’re using standard procedures to drive that change: high-level corporate communications followed by content deployment. In this environment, those standard methods will fail, not because the strategy is flawed, but because the human energy required to absorb it has been depleted. You need to change the energy and focus of the workforce before you can change behavior. Otherwise, you’re investing in transformation on top of shrinking execution capacity.

C-Suite: Is this primarily a white-collar phenomenon?

Cardoz: No. Numbness affects every organization and every team in distinct ways. Every large organization has change fatigue. The erosion of wonder in work, being tied to value and purpose, is common across white- and blue-collar employees. Even CEOs are feeling isolated. In a hybrid world, many don’t truly know their employees. Some are endorsing AI investments without a coherent AI strategy because of external pressure. This isn’t just an employee engagement issue. It’s a systemic constraint on performance and one that affects frontline workers, knowledge professionals, and executives alike.

C-Suite: What is your remedy?

Haywood: It’s sequential. Historically, organizations leap to what we call the “It” stage: this is what needs to change, these are the new capabilities, this is what you must do differently. But in Generation Numb, change is often heard as code for future layoffs. Organizations need to start with the “Me” stage, connecting change to personal priorities. What does this mean for me? Why should I engage? The key isn’t removing fear. CEOs can’t guarantee there won’t be layoffs. But they can create enough relevancy and meaning to build trust. One practical example is being explicit: if you develop these skills, you become more valuable — whether here or elsewhere. Then comes the “Us” stage, restoring connection and community. People are longing for that. Only after “Me” and “Us” can you effectively move to “It” and the initiative itself. Skip the sequence, and change may appear to move forward, but adoption will be shallow and fragile.

C-Suite: What does leadership need to do differently?

Cardoz: Authenticity is critical. There’s honesty in saying: we are in extraordinary change times. We’re changing today, and we’ll need to change tomorrow. Let’s talk about why. Have an adult-to-adult discussion. The other key is agency. Give people as much agency as feasible to define what that change looks like for them. When people have agency, they re-engage.

C-Suite: You’ve emphasized analog experiences in a digital age. Why?

Cardoz: We have a strong legacy in digital solutions. But clients have pushed us to experiment more with analog delivery. We ran a three-day workshop with a Fortune 100 brand entirely without technology - no laptops, no slides. One participant said, “I’ve forgotten that real work can happen outside a laptop.” Another said, “I’ve forgotten what it means to connect with peers in an authentic way.” We even took them to an aquarium and asked them to walk through in assigned customer personas. It unlocked empathy and imagination. These methods were tried and tested. They work precisely because the workforce is overly immersed in technology. In a digitally saturated environment, analog experiences can restore imagination, empathy, and human connection - the very ingredients transformation depends on. Of course, the C-suite has to consider budgets and scale. But we are finding that analog can be a powerful antidote to numbness.

C-Suite: Do you have any final advice for executives pursuing transformation?

Cardoz: Every organization says, “We want our people here,” and it’s usually a place of high performance. Leaders are trying to extract the final 10–15% of performance that becomes competitive advantage. They want to jump to “It” because of urgency and pressure. But their people just aren’t there yet. If you proceed along the Me–Us–It path, and recognize the stage your people are in, you can begin rebuilding them to a place where work becomes a badge of honor again, because they’re connected to their team and to the value of the work. That’s how you unlock the performance you’ve been chasing.

This was not a narrow statutory ruling. It redraws the boundary between presidential and congressional authority in trade policy and forces a recalibration of the Trump 47 administration’s geopolitical and economic strategy.

What the Court Decided and Why It Matters

IEEPA was enacted in 1977 to allow presidents to respond swiftly to national emergencies stemming from foreign threats. Historically, it has been used to freeze assets, block transactions, and impose sanctions. The statute nowhere explicitly mentions tariffs. The administration argued that its broad authority to “regulate” economic transactions included the power to levy import taxes. The Court disagreed, reasoning that tariffs are economically and politically consequential instruments that require clear congressional authorization.

The immediate consequence is clear: the administration’s fastest and most flexible tariff mechanism is no longer available, absent new legislation. The deeper consequence is structural. Emergency authority can no longer serve as a shortcut around the trade policy process. Tariffs remain very much in the policy arsenal, but their deployment will likely be slower, more procedurally constrained, and more legally contestable.

Why This Reshapes U.S. Trade Power

For the administration, rapid tariff announcements signaled resolve and created leverage. Without IEEPA, that shock capability is constrained. Trade actions will likely become more targeted, more bureaucratic, and more legally durable, but also slower.

For companies, the key takeaway is not that tariff risk has disappeared. It is that tariff risk has become more complex. The instrument has changed; the geopolitical tensions driving it have not.

There is also a fiscal dimension. If courts ultimately require reimbursement of tariffs collected under IEEPA, the federal government’s exposure could be substantial. The process would almost certainly be contested, slow, and administratively burdensome. Resolution could take years. In the interim, uncertainty will sit on corporate balance sheets and in federal budget projections alike.

Beyond the fiscal implications, the ruling has important consequences for the structure of North American trade.

USMCA Implications

For companies, the ruling’s potential implications for USMCA are particularly significant. North American supply chains are deeply integrated and rely heavily on the agreement’s rules of origin, tariff preferences, and dispute-settlement framework.

Conceptually, the decision does not materially increase the likelihood of USMCA’s dissolution. North American supply chains, especially in automotive, are trilateral by design, making a return to purely bilateral structures operationally disruptive. Moreover, replacing USMCA would require statutory authority and likely congressional involvement. A wholesale restructuring would impose substantial costs on U.S. firms.

Rather than abandoning USMCA altogether in favor of separate bilateral agreements, the more plausible path is incremental layering: sector-specific measures, side letters, tighter enforcement, and managed-trade adjustments. The agreement would formally remain intact, but operational complexity would rise. For companies operating across North America, that distinction matters.

Four Paths Forward

From a C-Suite perspective, four plausible scenarios emerge:

1) Compliance and Recalibration
The administration unwinds IEEPA-based tariffs and pivots to more defensible statutory authorities. Trade friction continues, but through slower and more procedural channels. Institutional credibility improves, but escalation capacity diminishes.

2) Reimposition Under Alternative Authority
Other statutes are invoked to reimpose tariffs in modified form. Foreign governments adopt a wait-and-see posture, calculating that U.S. measures could again be constrained by the courts. Legal challenges resume. Volatility persists.

3) Targeted, Industry-Specific Escalation
Rather than broad-based tariffs, the focus shifts to specific sectors, including automotive, steel, and semiconductors, under national security or trade enforcement authorities. Economic pressure becomes concentrated. Bargaining leverage increases, but so do retaliation risks and domestic political friction.

4) Legal Escalation and Institutional Conflict
Narrow compliance or aggressive reinterpretation triggers injunctions and prolonged legal confrontation. This is the least stable path. Markets respond quickly to signs of constitutional strain, and capital investment pauses follow.

The most coherent, and therefore most likely, outcome is a hybrid of the first and third paths: formal compliance with the ruling followed by targeted, sector-specific actions under clearer statutory authority. Tariffs will likely persist, but they will become narrower, more structured, and more legally grounded.

Why Automotive Sits at the Epicenter

Few industries illustrate the stakes more clearly than automotive. Modern auto supply chains are deeply integrated with components crossing borders multiple times before final assembly. Electric vehicle production adds further exposure through batteries and critical minerals. Just-in-time logistics magnify even minor disruptions.

Under a compliance-and-recalibration scenario, automakers may pursue tariff reimbursement claims while cautiously restoring cross-border efficiencies. Under sectoral escalation, autos and parts could become direct targets. Input costs would rise. Supply chains linked to Mexico and Canada would come under renewed pressure. Pricing strategies would require adjustment. Investment decisions on plant location and sourcing could accelerate.

In either case, the risk environment remains structurally elevated. The difference lies in duration and concentration. Broad volatility affects many sectors moderately. Sectoral targeting affects fewer players intensely.

How Senior Leaders Should Respond

The Supreme Court’s decision did not end the era of contested trade policy. It changed its operating system. Emergency-based tariff shocks are less viable. Structured, legally grounded trade actions are more likely. Near-term volatility will persist as policymakers recalibrate and litigants test the limits.

For senior executives, the imperative is not to forecast the next headline. It is to build strategic, financial, and operational resilience. The right question is not “Will tariffs return?” but “How resilient is our operating model across multiple tariff regimes?”

Companies should map exposure across products and markets; stress-test margins under varying tariff levels and durations; sequence capital allocation to preserve optionality; and engage proactively in coordinated policy advocacy where sectoral risks are rising.

Trade policy will remain a strategic variable. It will now unfold through more formal channels, over longer timelines, and with greater institutional friction. The phase of emergency tariff shocks may be narrowing, but the phase of structural trade tension is not.

• The agreement modestly narrows, but does not eliminate, the labor cost gap between VW Chattanooga and the Detroit 3.

• Lengthy negotiations and tangible gains bolster UAW credibility with VW workers.

• The contract follows standard UAW patterns; there is no Works Council–style governance or evidence of coordination with IG Metall.

• Volkswagen’s refusal to align contract expiration with May 1, 2028 weakens UAW ambitions for coordinated national action.

• Foreign-owned OEMs may raise wages preemptively; rapid unionization momentum remains unlikely.

I. What Changes

UAW credibility at foreign-owned plants. The agreement was hard-fought. After Volkswagen cut a shift in response to soft EV demand, the UAW filed an unfair labor practice charge, rejected a “best and final” offer, and secured strike authorization. The resulting deal includes stronger job protections, bonuses, and other gains beyond Volkswagen’s final offer. These outcomes strengthen the UAW’s standing with Chattanooga workers and validate Fain’s post-2023 organizing strategy.

Marginal labor cost convergence. The contract includes a roughly 20% wage increase, COLA, bonuses, and reduced healthcare costs. Still, top pay for VW workers will remain under $40/hour even in 2030, compared with $43/hour at the Detroit 3 by 2028, and VW workers will take longer than those at the Detroit 3 to reach that level. Bonuses lag recent Detroit 3 profit-sharing checks, and the all-in labor cost gap may remain around $20/hour. This narrows, but does not erase, the structural cost advantage of Volkswagen relative to the Detroit 3 and opens a gap between VW and other foreign OEMs.

II. What Doesn’t Change

Governance and decision rights. The agreement appears conventional, with standard language on work rules, grievances, outsourcing, and job security. These terms constrain management decision-making and help explain why foreign OEMs, like many other employers, resist unionization. However, there is no indication of union participation in operational decision-making akin to a Works Council. Nor is there evidence of coordination with IG Metall during bargaining; notably, the UAW did not publicly express solidarity when Volkswagen announced restructuring in Germany.

National coordination of labor action. The UAW sought to align the Volkswagen contract expiration with the Detroit 3 on May 1, 2028, a key element of Fain’s ambition for coordinated national action. Volkswagen refused, and the agreement now runs to 2030. Aside from limited signals from the SEIU, there is little evidence that a cross-union alignment strategy is taking hold.

III. Implications for unionization in the South

When the UAW won the Chattanooga vote, two strategic paths for further unionization gains emerged:

1. The “Dominoes Game”: building momentum plant by plant through successive organizing wins.

2. The “Contract Game”: using a strong Volkswagen agreement to persuade workers elsewhere that unionization delivers tangible gains.

The Dominoes strategy stalled after UAW losses at Mercedes plants in the South in the spring of 2024. Whether the UAW now invests heavily in the Contract Game remains unclear. The prolonged Volkswagen negotiations, a less union-friendly NLRB under the Trump Administration, and internal UAW distractions may limit appetite for an aggressive push. Fain may instead declare victory, focus on reelection, and conserve resources for 2028.

That said, the agreement will not go unnoticed. As after the 2023 Detroit 3 contracts, foreign automakers may choose to raise wages proactively to reduce union risk.

IV. The bottom line

The Volkswagen-UAW agreement represents a symbolic and political win for the UAW, but merely a limited structural shift for the industry. It modestly compresses labor cost differentials, clarifies the bounds of union influence at foreign-owned plants, and improves Shawn Fain’s chances of reelection. If Fain remains in office, executives should expect a renewed, and potentially disruptive, push at the Detroit 3 in 2028 - likely involving escalated strike tactics aimed at reversing long-standing retirement concessions. Planning for that risk should begin now.

A year ago, we argued that the events of 2024 had effectively answered seven major questions - each a lens into the political, economic, social, and technological forces shaping the global business environment. Those answers did not bring clarity or stability. Instead, they set the conditions for the five most consequential business developments of 2025, which we review here as our annual recap of the year’s defining trends.

2025: A Surprising Year That Shouldn’t Have Been

2025 was, by any measure, another eventful year. Uncertainty deepened, volatility intensified, and periods of apparent stability were repeatedly punctured by disruption and, at times, outright chaos. The single most consequential event was, of course, the re-election of Donald Trump as President of the United States, an outcome whose implications extended far beyond U.S. borders. The new administration’s markedly different perspective on trade, regulation, climate policy, immigration, and the global order reverberated across industries and geographies.

Many companies were initially caught off guard but still responded effectively, drawing on crisis playbooks refined through years of disruption from the first U.S.–China trade war and the pandemic to the semiconductor shortage. They built inventory buffers, rerouted supply chains, curtailed discretionary spending, and postponed high-commitment decisions. Pricing discipline largely held, though at the expense of margins. But as the year progressed and shocks accumulated rather than dissipated, many leadership teams found themselves uncertain about what to do next. Tactical resilience proved easier to master than strategic direction.

None of this should have come as a surprise. In a C-suite article we published in July 2024 -well before President Biden withdrew from the election - we examined the implications of a potential Republican sweep. That analysis anticipated the core dynamics that came to define 2025: an intensified “America First” posture, rising trade barriers, continued U.S.–China tensions, regulatory rollbacks (particularly on environmental issues), tighter labor markets driven by immigration policy, and renewed pressure on global institutions as the U.S. implicitly enabled a more multipolar world order. We also outlined the second-order effects: inflation volatility, supply-chain realignment, and uneven sectoral outcomes, especially in green technologies and AI.

Importantly, these were not predictions in the conventional sense. They emerged from a disciplined examination of underlying drivers and incentives - an approach that often produces outcomes that align more closely with reality than formal forecasts do.

Against that backdrop, we turn to our perspective on the five most important business developments of 2025: why they mattered and what they imply for C-suite leaders looking ahead.

1. Geopolitics and the New World Trade Order

The defining macroeconomic reality of 2025 was not recession or recovery, but fragmentation. As we wrote previously, “with trade increasingly seen as a tool of industrial and foreign policy, global supply chains face massive disruption.” In 2025, that disruption moved decisively from theory to operating reality.

The Trump administration’s sweeping tariffs pushed the U.S. effective import tax rate to levels not seen since the 1930s. Tariffs became less about trade balances and more about leverage, forcing companies to reassess not only where they source and manufacture, but which markets they can reliably serve at all.

A direct confrontation with China exposed a structural asymmetry at the heart of the global economy. Washington’s tariff threats - ranging from 25% to well above 100% on selected imports - were met not with capitulation but with targeted retaliation. Beijing’s response, including export controls on critical rare-earth materials and abrupt halts to U.S. agricultural purchases, underscored that geopolitical leverage increasingly rests on control of bottlenecks, not just trade volumes.

Crucially, the fallout did not remain bilateral. As we warned earlier, “if a tariff spiral does ensue, the indirect spillover effects would likely be significant as well.” Reduced Chinese access to the U.S. market flooded the EU and parts of Latin America with excess capacity, triggering defensive measures across industries such as steel, chemicals, EV components, and industrial machinery. The result was an acceleration toward a more transactional, regionalized trade system.

Geopolitical instability compounded these pressures. Iran’s sharply weakened position, following Israeli military actions and the collapse of much of its proxy network, reshaped Middle Eastern power dynamics. As we noted previously, this raised the risk of broader regional escalation involving the U.S. and other Western powers. For global businesses, the impact was immediate: renewed energy market volatility, higher insurance and logistics costs, and persistent uncertainty around shipping routes and regional investments.

At the same time, the multilateral institutions required for managing systemic risk appeared increasingly fragile. “NATO and the EU, weakened by recent elections, lack cohesion,” limiting Europe’s ability to act as a stabilizing force in security or economic policy. For multinational firms, this meant navigating a patchwork of national responses rather than a coordinated transatlantic approach, particularly in industrial subsidies, defense spending, and trade enforcement. Europe increasingly combined regulatory weight with diminishing growth momentum, an uncomfortable mix for global firms.

Importantly, strain was not confined to emerging markets. “Even North America feels the strain,” as hardline trade and immigration policies amplified uncertainty across U.S.–Mexico–Canada supply chains and intensified labor shortages in logistics, agriculture, and manufacturing.

For the C-suite, the lesson was clear: assumptions of a stable, rules-based global trade system no longer hold. Competitive advantage now depends less on global optimization and more on geopolitical resilience – i.e., supply-chain redundancy, regional manufacturing strategies, and the ability to pivot quickly as trade and foreign policy collide.

2. Economic Resilience Masks a Deepening K-Shaped Recovery

Despite trade turbulence and geopolitical shocks, the U.S. economy proved remarkably resilient. Beneath the surface, however, a K-shaped recovery deepened. Higher-income households continued to spend, while lower-income households faced persistent cost-of-living pressures. In the short term, this divergence sustained aggregate demand. Over the long term, it raises more troubling social and economic questions.

The labor market tells the story. Headline employment remained stable, but hiring slowed markedly, creating a “low-hire, low-fire” environment. Job prospects deteriorated sharply for new college graduates as firms delayed expansion and AI reduced demand for entry-level roles.

At the other end of the spectrum, labor shortages intensified in manufacturing, construction, healthcare, logistics, and agriculture. These shortages were not cyclical but structural, driven by reduced immigration flows, large-scale deportations, and underinvestment in vocational training and reskilling programs.

More concerning still was the erosion of the U.S. as a global talent magnet. Visa crackdowns, higher fees, longer processing times, and a more hostile political climate made the U.S. less attractive to STEM professionals and researchers. For decades, innovation leadership rested on this advantage. In 2025, it began to weaken visibly as top candidates increasingly chose Europe, Canada, or parts of Asia.

For business leaders, the implication is clear: workforce strategy is no longer an HR concern. It is a core element of competitive positioning, productivity, and long-term innovation capacity.

3. AI’s Breakout Year—and Why Value Remained Elusive

2025 was AI’s breakout year. Adoption accelerated, investment surged, and AI moved from experimentation to deployment. Yet for most companies, results fell well short of expectations as multiple studies suggested that as many as 90–95% of corporate AI initiatives failed to deliver meaningful business impact.

History offers a parallel. During the dot-com boom, digital technologies diffused rapidly, but productivity gains lagged for years – i.e., the Solow Paradox. The lesson was not technological but organizational. As we have written previously, organizational change and public policy ultimately shaped the trajectory of past technological revolutions far more than the technologies themselves.

Most AI failures share a common root cause: attempts to layer AI onto legacy structures, processes, and incentives. AI teams often operate in isolation, disconnected from business units, lacking decision rights, clean data, or sustained executive sponsorship.

Public policy adds another layer of complexity. Governments oscillate between promoting AI as a growth engine and constraining it due to concerns over privacy, bias, labor displacement, and national security. As we have noted before, “the future of digital transformation depends on what happens inside organizations and in the external policy environment, not just on the technology itself.”

The implication for executives is clear: AI advantage will accrue not to the early adopters, but to firms willing to redesign how work gets done.

4. The EV Reversal, Energy Policy Whiplash, and the China Question

After years of regulatory momentum, 2025 marked a clear inflection point in the U.S. energy transition. Rollbacks of EV subsidies and renewed support for fossil fuels reshaped investment economics almost overnight. Automakers, utilities, and suppliers were forced to reassess demand trajectories, infrastructure plans, and capital allocation.

The slowdown in EV adoption also reflected a familiar adoption “chasm.” Early adopters were largely saturated, while the early majority remained hesitant due to cost, infrastructure gaps, and resale concerns. This domestic hesitation intersects with a more strategic issue: the rise of Chinese EV manufacturers. As we argued earlier, the threat hinges on two variables: U.S. EV adoption and Chinese market access. In 2025, both became clearer. Firms like BYD demonstrated that they are not theoretical competitors but proven global players, combining vertical integration with aggressive cost advantages.

Mexico emerged as a strategic wildcard. By leveraging USMCA provisions, Chinese OEMs positioned themselves to serve price-sensitive segments, initially with ICE and hybrid vehicles, and potentially EVs later. The risk for U.S. incumbents is not immediate collapse, but strategic drift, leaving them underprepared if adoption reaccelerates and market access widens simultaneously.

The broader lesson extends beyond autos. Energy transitions are no longer linear or globally synchronized. They are politicized, uneven, and competitively disruptive.

5. Populism, Governance, and the Limits of the Old Order

2025 confirmed that populism is no longer a reaction - it has become a governing force. As populist movements transitioned from opposition to administration, internal contradictions became visible. Governing requires compromise, prioritization, and administrative capacity - qualities often at odds with populism’s mobilizing logic.

Across advanced economies, these tensions surfaced repeatedly. Coalitions forged in opposition proved difficult to sustain once policy choices imposed real costs. Protectionism collided with inflation control; immigration crackdowns worsened labor shortages; fiscal populism ran into debt constraints. For businesses, this represents a structural increase in political risk across markets once considered stable. The challenge is no longer how to wait out populism, but how to operate in an environment of fragmented legitimacy and uneven governance capacity.

Strategic Takeaways for C-Suite Executives

If 2025 demonstrated anything, it is that volatility is no longer an aberration - it is the new baseline.

First, enterprise risk must be mapped globally and dynamically. JIT supply chains optimized for efficiency have become structurally fragile.

Second, executives must plan for divergent consumer segments and labor realities shaped by uneven adoption, constrained talent supply, and shifting migration patterns.

Third, technology creates value only when paired with organizational change and governance. Tools alone are insufficient.

Fourth, energy and climate policy uncertainty must be incorporated into capital planning. Linear transition assumptions are no longer viable.

Finally, populism has moved from protest to power without fully replacing the old order, creating regulatory fragmentation that demands rigorous stress-testing.

If 2025 was the year companies absorbed this reality, 2026 will be about translating reactive resilience into proactive foresight and strategy. Ultimately, the organizations that succeed will stop waiting for clarity and instead build the organizational capabilities and processes needed to perform consistently across volatility and uncertainty.

References

Are Chinese EV Makers an Existential Threat to U.S. Legacy Automakers?, Jul ‘25

The Rare-Earth Chokehold, Jun ‘25

Seeing Around Corners, Mar ‘25

2024 Questions Revisited - Looking Back and Looking Ahead, Jan ‘25

Preparing for Trade Disruptions, Dec ‘24

Prestige vs. Dominance: Leadership Matters in the U.S. Presidential Election, Nov ‘24

The Electric Vehicle Slowdown: A Lesson in Technology Diffusion and Saddle Patterns, Aug ‘24

Strategic Planning for U.S. Election Scenarios, Jul ‘24

2024 – The Year Questions Become Answers, Feb ‘24

Turbulence Ahead: US-China Relations in a Shifting Landscape, Sep ‘23

Scenarios for the Future of AI and Digital Transformation, Jun ‘23

Learning from the History of Technological Revolutions, May ‘23

Eric Gertler has led organizations across the media landscape, from the New York Daily News to U.S. News & World Report, during one of the most volatile periods in the industry’s history. Under his leadership, U.S. News has undergone a profound transformation from a money-losing print magazine into a highly profitable digital platform. We spoke with Gertler about what has driven that transformation and the lessons it holds for executives in any industry. (Gertler has also held high level leadership roles in government and philanthropy.)

C-Suite: Eric, U.S. News has changed dramatically under your tenure. What has guided your decisions and what lessons might apply beyond media?

I have had the privilege of leading a brand that has been around for over 90 years. Of course, the world has changed a lot over those 90 years and so we have had to evolve ourselves accordingly.

We have gone from a money-losing print magazine to a highly profitable, robust digital marketing platform. To do that, we have had to understand and stay true to our values, starting with a clear North Star: helping our consumers make the most important decisions in their lives. It doesn’t really matter whether we are doing that in print or any other distribution format.

Equally important has been integrity about what we produce, write, and distribute. We have maintained a high quality level of the editorial content we produce while ensuring that our editorial team operates free from business interference, which reinforces the high degree of credibility that we enjoy. And that credibility has been essential as we expanded into areas like education, healthcare, business, money, autos, and travel. Today, we focus heavily on important consumer news that affects people’s lives – it is critical that people know that they can trust the information we provide, which reinforces the trust in our brand; that trust has been the foundation for our growth.

We have also transformed into a data and information business and that is not obvious at all for a journalism company. We receive a lot of respect for our rankings of colleges as well as for our rankings on best hospitals. And that is impressive, as, in one sense, there can only be one winner in a category. But we are able to stand behind our rankings because of the rigor, transparency, and integrity of our methodology. Competitors may try to replicate them, but our commitment to accuracy and clarity really does set us apart.

C-Suite: What is your leadership style in that context? Has it evolved as you’ve navigated the structural shifts?

My leadership style has definitely evolved, though probably more from moving back and forth between the public sector and the private sector than from managing a private company alone.

Having led in the private sector first made me a better leader in public service because I understood what really matters there: execution and getting things done right. Public service, on the other hand, requires much more collaboration. You are operating in three dimensions and constantly factoring in public opinion. When I returned to the private sector, I brought that mindset with me and became a more collaborative CEO.

Another big lesson from public service is scale. The projects are so large that you have to learn to focus on what truly matters and avoid micromanaging. That is especially true when you are transforming a media company in the middle of significant turmoil. You need the right people in the right seats, moving in the same direction, and you simply cannot manage everything yourself. There is too much going on.

I have learned to trust and empower my team. If there is a crisis or a conflict between two areas of the company, I get involved. Otherwise, you need to set a direction and ensure you have the right people to execute well and use good judgment, because no single person can do it all.

C-Suite: AI is transforming the entire media landscape. What parts of media will AI fundamentally reshape and which parts will remain human for longer than people expect?

We are probably still in the very first inning of AI’s impact. AI is already having a dramatic effect on businesses, both because of what it is actually doing and because of how leaders perceive what it will do.

Google has historically been the main funnel driving traffic to digital media companies. But as it increasingly relies on AI-generated overviews that aggregate content, fewer users are clicking through to individual sites. That fundamentally undermines the economics of a media business: fewer eyeballs, fewer consumers, and less value for advertisers or performance marketing. If you look at large media companies that depend heavily on Google, many have seen traffic declines of 25% to 50% over the past year. That’s dramatic.

On the flip side, there is the real, constructive impact of AI. We, and many others, are using AI to improve products so that when users do come to the site, they get a much more valuable experience.

The big question, of course, is whether AI replaces journalists and the content media companies produce. The answer is not yet, but it is coming faster than most people are prepared to accept. We are already seeing AI used in parts of the process: helping journalists with research, background, and editing. Still, we have our journalists reviewing any part of our AI usage.

Then there is what I would call the perceived effect. That occurs when leaders start changing their businesses based on what they think AI will be able to do, even though the technology is not actually there yet. You end up making big decisions without fully understanding what the real impact will be.

There’s also great irony here. Many of the AI systems were trained on the journalism and content created by media companies. Yet some of those same media companies may not exist in the future, while these AI companies will still need that content to keep learning and improving. I think the AI companies are starting to recognize that, which is why you’re now seeing so many content deals happening. In many cases, it’s been a matter of “better to beg for forgiveness than ask for permission,” because without that content, these systems never would have reached their current level of intelligence.

But, I assume every part of our business will be affected either positively or negatively. What I have emphasized internally is that, through this transformation, when consumers see our brand, they need to trust what we are doing. Whether it is AI-enabled products or intelligent bots on our site, people should know that when they see the U.S. News logo, they can rely on what we put in front of them.

C-Suite: What are the most difficult transformation decisions?

The hardest decisions always involve people. Everything else is just working through a problem. With people, there are emotional attachments and long-standing relationships. If, as a CEO, you no longer feel emotion when you are letting people go, then you have probably stayed too long.

Even in a world of increasing technology, you have to respect the individuals in your organization. The real challenge is deciding who to empower to lead the transformation, who can be reskilled or redirected into growth areas, and who ultimately has to be let go. We recently let someone go who had been with the company for decades. Those are incredibly difficult decisions.

We try to handle those moments with dignity, because what matters most to me is respecting the people who have given their time and energy to the company. And, if you have a talented person on your team and they leave for another opportunity, that is a failure as a CEO.

C-Suite: You’ve mentioned that rankings are a major differentiator for U.S. News. In the age of AI, how do you protect that asset?

You can see differentiations today in how journalism, in a broad sense, is perceived today. A media company like ours or The Wall Street Journal, for example, has built its brand on integrity and high reporting standards. At the same time, many young people get their news from TikTok, meaning content with no context, questionable accuracy, and little or no sourcing. People may turn to either social media or traditional media, but the hope is they understand there is a greater level of trust, context, and reliability with a brand like ours or the Journal.

The same applies to rankings. You can ask an AI tool for a “top” list and get an answer, but you do not know the context or the methodology. Can you trust it? Has it been reviewed? Is it right for you?

We are still at a point where people want a credible brand standing behind the rankings and a thoughtful evaluation process they can understand. And rankings are not simply a list. Consumers can slice and dice them based on important criteria like, for our education rankings, debt levels, best schools for veterans, or HBCUs. There is also an element of accountability for the institutions themselves. The institutions must understand the process and see it as credible.

We may be living in a new technology-driven world, but when people see our brand, they know the serious work that is behind anything that we publish. They know there is a methodology they can read and evaluate for themselves. When you are making consequential decisions, about hospitals, higher education, or more, the source really does matter.

C-Suite: This has been a turbulent year for higher education, including increased politicization. How are you dealing with that at U.S. News?

We have stayed focused on what we do best: outcome-driven rankings. We ask fundamental questions. Is the university graduating its students? Are students graduating with manageable debt? Those are the two most important questions facing higher education today.

There are thousands of universities, and for decades they promised that a degree would lead to a better, more prosperous life. For many people, that has not happened over the last 15 years. That is why trust in universities has dropped from around 70% to the mid 30% range. It also explains why enrollment has declined. Today, we have roughly 40 million Americans with some college education, no degree, and student debt. Many feel the system has failed them.

The real workhorses of higher education are public universities and community colleges. What gets most of the attention, though, are the elite institutions, which I believe have shifted in some cases from being purely educational to partly ideological. They have moved away, in part, from teaching students how to think toward telling students what to think.

I have had public disagreements with some of the institutions at the top of our rankings. I have consistently said two things. First, when colleges charge this high level of tuition, they owe students full transparency so families can make informed decisions. Second, colleges must be accountable. Many institutions, especially elite ones, have operated behind ivory towers and grown disconnected from broader society. There has been a lot of good in that, but there has also been a loss of accountability.

Parents and governments are now saying they do not want to continue to provide funding without clear expectations being met. Whether those expectations are right or wrong, we live in a world where transparency and accountability matter, and that applies to everyone.

C-Suite: We’ve covered a lot of ground. What lessons would you want to share with C-suite leaders in other industries?

I am always looking for lessons from other leaders myself. When I think about what has driven the success of U.S. News, a big part of it is that we have been able to build businesses across multiple categories: news, health, education, money and insurance, small business, travel, autos, and product reviews. That diversity has allowed us to grow and become very profitable.

The first piece of advice is to prioritize areas that offer the greatest potential return and are fully aligned with your brand. In a time of transformation, you have to ask: where do you get the biggest bang for the buck? You simply cannot do everything.

The second lesson is to put execution ahead of strategy. Strategy gives you direction, but real learning happens through execution. You have to be willing to launch, test, make mistakes, and learn from the market.

Third, CEOs need to stop thinking they have all the answers. We have moved from a top-down world to one driven by bottom-up learning. Organizations perform best when ideas come from everywhere, especially from people on the front lines or those new to the company. If you can create mechanisms to surface and act on those ideas, the company performs infinitely better.

Finally, as a CEO, give the credit away to others. Even better, do it publicly. It motivates your employees and the company. You benefit anyway if others perform well.

Welcome to the second issue of our economic and business roundup. Each month we focus on the top 3–5 forces shaping markets, geopolitics, and corporate decision-making. This month, the common thread is policy divergence and structural uncertainty, creating a more volatile and less predictable operating environment.

1) The U.S. Economy: Soft Landing, Tight Supply, and Policy Volatility

The U.S. economic growth is increasingly uneven (i.e., “K-shaped”) with higher‑income groups advancing while lower‑income workers fall further behind. Consumer sentiment remains below prior levels as households grapple with high prices and labor‑market uncertainty. Nevertheless, overall consumer spending and services are holding up for now while inflation seems to be easing toward the Fed’s 2% target. Interest rates remain elevated, but further rate cuts are a near-certainty after Powell departs next year.

Key structural pressures:

• Labor constraints: Economic growth slowed by talent shortages across sectors (e.g., logistics, construction, healthcare), compounded by a net outflow of immigrants and the retirement of baby boomers

• Capital costs: Borrowing remains expensive, limiting investment

• Fiscal trajectory: High deficits introduce uncertainty for interest rates, bond markets, and public-sector contracts

• Policy volatility: Upcoming elections and regulatory shifts could affect taxes, industrial policies, immigration, and environmental compliance

Bottom Line: While the economy appears relatively stable on the surface, C-Suite executives should anticipate intermittent shocks, a tightening labor supply, and persistent volatility in fiscal and regulatory policy, alongside the looming risk of asset bubbles deflating across stocks, crypto, AI, and housing.

2) The Supreme Court Tariff Case: Potential Realignment of U.S. Trade Authority

The Supreme Court is set to rule on Presidential tariff authority. This decision will shape whether the White House retains unilateral control or whether Congress reclaims a significant role.

Potential outcomes and second-order effects:

• Limited authority: More predictable tariffs, slower deployment, fewer surprises

• Expanded authority: Accelerated tariffs, retaliatory measures, inflation pass-through, and supply chain disruptions

Retroactive implications: If SCOTUS rules against the Administration and tariff payments already made must be refunded, companies could face a temporary windfall, but also substantial operational uncertainty as customs authorities determine how refunds are processed. Large retailers and importers may need to manage complex accounting adjustments, potentially impacting cash flow and quarterly results. At the same time, the ruling could trigger pressure to reinstate tariffs under a new framework, creating further decision-making complexity.

Bottom Line: Tariffs will remain a major source of policy uncertainty. Companies should scenario-plan for sudden shifts in sourcing, pricing, and logistics now to avoid scrambling for operational or financial adjustments later.

3) Climate Policy Divergence: Fragmentation, Governance, and Capital Allocation

Global climate policy is diverging rather than converging, with the U.S., EU, and China moving on different trajectories that create regulatory and operational complexity: The U.S. is implementing a (temporary?) policy reversal, the EU is facing implementation delays, and China is pressing ahead at full speed.

Key dynamics:

• U.S.: Litigation and political pressure complicate SEC climate disclosure and emissions standards; California continues to enforce stricter rules

• EU: Aggressive emissions targets, carbon border adjustments, and CSRD reporting requirements continue but with increasing resistance

• China: Focused on competitiveness and standards-setting in EVs, batteries, and solar

Business implications:

• Boards face increasing fiduciary responsibilities around climate disclosure

• Capital investment and insurance costs are rising due to extreme weather, infrastructure constraints, and retreating coverage

• Multi-jurisdictional compliance is costly and will persist for the next decade

Bottom Line: Climate is no longer a long-term horizon issue but a medium-term operational and strategic constraint.

4) Japan–China Tensions: Economic Rivalry, Strategic Risk, and Supply Chain Exposure

Tensions in East Asia are intensifying not only due to Japan’s military modernization and China’s assertive regional posture, but also because of the role of Japan’s new Prime Minister Sanae Takaichi, whose hardline stance on Taiwan and accelerated defense agenda have further sharpened regional frictions.

Key points:

• Red lines remain fragile: Taiwan independence continues to be China’s ultimate non-negotiable red line

• Alliance dynamics: U.S. guarantees shape Japanese actions and influence regional signaling

• Operational exposure: Semiconductors, battery materials, precision machinery, and shipping lanes are vulnerable to disruption

Bottom Line: Geopolitical risk is unlikely to escalate to conflict in the short term, but supply chain and trade disruptions are increasingly probable. Scenario analysis remains essential.

5) Autonomous Vehicles: The Shift from Hype to Practical Deployment?

The AV landscape appears to be moving from hype to selective, practical deployment. Funding and deployment are now concentrated among a smaller set of players such as Waymo, Tesla, and key Chinese operators.

Key dynamics:

• Safety outcomes: Recent high-quality studies suggest significant safety benefits for Waymo AVs compared with human drivers in deployed areas

• Economics: Robotaxi unit economics remain challenging; middle-mile and freight applications show clearer ROI

• Regulatory fragmentation: Different U.S. states impose varying safety, testing, and liability requirements

• AI oversight: 2025 executive orders increase scrutiny on safety-critical AI systems

Caution: The automotive industry has a long-standing tendency to go “all-in” on emerging trends (e.g., EVs, AVs, fuel cells, telematics, M&A) only to encounter setbacks when reality invariably catches up with the hype. AVs are especially sensitive, subject to intense scrutiny and widespread media attention, where even a single high‑profile incident can derail public acceptance and regulatory progress, impacting not just individual companies but the entire sector (e.g., Cruise, Tesla, Uber).

Strategic implication: A more thoughtful, scenario-based approach is essential. Companies should consider a range of plausible outcomes rather than relying on most-likely or best-guess forecasts, especially for AVs where technological, regulatory, and public perception risks remain high.

Bottom Line: AV adoption is real but incremental. Executives should invest selectively, partner strategically, and avoid overcommitting capital until the sector demonstrates sustained, scalable performance.

Key Take-Aways

• Expect divergence, not convergence. Macro, trade, climate, and geopolitical policies are moving in different directions across regions

• Scenario analysis is critical. Model multiple economic, policy, and supply chain scenarios to maintain optionality

• Build operational resilience. Labor, energy, insurance, and capital constraints require flexible contracts and adaptive sourcing

• Strategic capital allocation: Prioritize investments with optionality, resilience, or early-mover advantages, while avoiding overcommitment to high-risk, unproven technologies

• Geopolitical vigilance: East Asia, trade enforcement, and climate regulations remain the highest-consequence risk zones

Each episode begins with an introductory meeting between Ramsay and the star-struck restaurant owner and his staff. Following an initial exchange of pleasantries - where the hapless restaurateur explains his misfortune and gratefully pledges to place the future of his business in the experienced hands of our intrepid chef - the fun begins, as Ramsay sits down to enjoy his first meal. Whether through dumb luck, sheer brilliance, or, more likely, clever pre-screening by his production team, Ramsay invariably selects the one dish the restaurant’s own chef doesn’t know how to prepare, and, with that, our first “moment of truth” has arrived; nervous waitresses and a completely befuddled chef begin to panic as an obviously perturbed Ramsay takes a few bites, refuses to eat any further, and orders something else from the menu instead - usually with equally disastrous results.

Having established that the restaurant’s poor financial results may just be a function of the owner and staff’s own incompetence - instead of “market forces” beyond their control - chef Ramsay proceeds to create the proverbial “burning platform” for fundamental change. This is usually by far the most entertaining part of the show, when, spoiling for a good fight, Ramsay lets loose in a foul-mouthed tirade designed to positively scare the restaurant crew out of their collective wits - while simultaneously serving up a generous portion of “schadenfreude” to the television audience at home - but also with the desired effect of shaking the organization out of its ingrained bad habits: invariably the food is absolutely terrible, the ingredients artificial, the menu a joke, the restaurant concept incomprehensible, processes non-existent, and cleanliness so poor that, in the words of our chef, “people may die here tonight!”

With the initial Diagnostic phase completed, and the “need for change” firmly established, Ramsay now sets out by himself to do some market and customer research. He walks around the neighborhood, checking out “latent demand” for potential new restaurant concepts. Once a potentially more competitive “value proposition” has been identified, Ramsay and his team completely remodel the restaurant overnight to “shock and awe” the ecstatic owner and his staff. The new repositioning concept is explained. We get a tour of the newly remodeled restaurant and anxiously await opening night. This is usually still touch-and-go, as the restaurant staff valiantly try to adapt to their new environment, but, with in-kitchen and on-the-floor help from the good chef himself, all ends well, and the show concludes with lots of hugs, kisses, and a tearful goodbye.

So there you have it. All the ingredients for a successful business turnaround are there: fresh market and customer research as the main ingredients, a main course of successfully repositioned products, served in newly refurbished and rebranded facilities, all lovingly prepared on a clear mandate for fundamental change, and, of course, deliciously entertaining. Bon appétit and Happy Thanksgiving!

US-China relations have entered their most consequential period since Nixon’s diplomatic overture in the 1970s. As tensions mount over semiconductors, data, clean energy, and rare earths, many Western executives - and policymakers - continue to rely on oversimplified narratives: that Chinese state-owned enterprises dominate the economy, that Beijing controls every decision, that Chinese firms merely copy Western technology, that China’s financial system mirrors ours, or that younger Chinese workers lack ambition.

These myths distort strategic judgment at a moment when companies must assess technology exposure, supply chain vulnerabilities, capital allocation, and competitive positioning. Executives need a clearer lens to anticipate how the bilateral relationship may evolve from accommodation or ongoing tit-for-tat competition, or, less likely, outright hostility.

Each scenario implies a materially different business environment: technology standards, tariff regimes, supply chain structures, investment rules, and regulatory burdens all shift depending on geopolitical trajectory. Companies need planning assumptions for all, not just the one they prefer. But effective planning requires accurate information and that begins with retiring persistent myths that misrepresent China’s economy and society.

Myth 1: China’s Corporate Sector Is Dominated by State-Owned Enterprises

State-owned enterprises (SOEs) are visible symbols of the state and key tools of industrial policy. But the notion that they dominate the economy is outdated.

Private firms were negligible in 1990; today they generate more than half of GDP and over 80% of urban employment. Companies like Huawei, BYD, CATL, and DJI have become global leaders without being traditional SOEs. Their rise reflects entrepreneurial dynamism, albeit often supported unofficially by local governments under pressure to hit growth targets.

This “state–private symbiosis” has produced world-class companies, regulatory arbitrage, and at times corruption. Western executives cannot assume that doing business in China primarily involves navigating monolithic, centrally controlled SOEs.

So what: Competitive benchmarking, partner selection, and market-entry strategies should focus far more on private-sector capabilities, and on understanding local government incentives, than many Western firms currently do.

Myth 2: The Central Government Dictates All Economic Activity

While Beijing does set national priorities, China’s political economy is far more decentralized than many assume.

Provincial and municipal leaders control land use, industrial parks, licensing, and local finance. Their careers depend on GDP growth and social stability, creating incentives to support investment, even if it requires bending or stretching national rules. For two decades, local authorities leveraged land ownership to fuel development, driving rapid growth while institutionalizing corruption.

President Xi’s anti-corruption campaign remains enforcement-focused rather than structural. Local officials continue to balance compliance with central directives against pressure to meet local objectives.

So what: Many companies misjudge political risk by focusing exclusively on Beijing rather than the provincial or municipal level where day-to-day decisions are made.

Myth 3: China’s Financial System Resembles the West’s

China has large banks and stock markets, but the comparison ends there.

All major banks are state-controlled, directly or indirectly. Lending is often policy-driven, with the state implicitly guaranteeing the system. Equity markets require regulatory approval for listings; companies must show consistent profits, and related-party transactions are common. As a result, stock market performance is weakly correlated with economic growth.

Tight capital controls limit overseas investment, leaving housing as one of the few assets available for wealth accumulation - a factor contributing to the country’s real estate imbalances.

So what: Western firms cannot rely on traditional financial indicators, such as equity valuations, bank lending patterns, or corporate disclosures, to assess risk. On-the-ground fundamentals and political context matter more.

Myth 4: China Copies Rather Than Innovates

China’s early development relied heavily on reverse engineering and technology transfer. That era has passed.

China now leads globally in electric vehicles, batteries, solar energy, drones, robotics, fintech, and increasingly AI. Its strength lies not just in invention but in rapid iteration, commercialization, and scaling - a capability often more important than ground-up invention.

Chinese consumers accelerate this cycle. They are tech-savvy, open to experimentation, and less constrained by legacy systems, enabling companies like Meituan, Pinduoduo, and ByteDance to prototype, test, and deploy innovations at speeds Western firms rarely achieve.

So what: In many sectors, Chinese firms are no longer fast followers but front-runners shaping global standards.

Myth 5: Millennials and Gen Z Are Spoiled Only Children

The stereotype of pampered or complacent younger generations is misleading – at least in China and probably elsewhere as well.

Chinese families invest heavily in education which is often a majority of household income. Cultural norms around duty and filial piety remain powerful. In a competitive marriage market, career success and financial stability carry outsized importance.

The result is young professionals who are ambitious, entrepreneurial, and willing to work extremely hard. The “9-9-6” ethos (9 a.m. to 9 p.m., six days a week) remains deeply ingrained despite regulatory pushback.

So what: Talent strategies assuming Western-style attitudes toward work, incentives, or mobility will misfire. Chinese teams respond to different pressures, cultural expectations, and motivations.

Seeing China Clearly

The US-China relationship will likely remain the world’s most important, uncertain, and volatile geopolitical force. Executives must anchor decisions in accurate assumptions, not outdated myths, which create strategic blind spots at a moment when precision matters most. Success will go to those leaders who see China clearly - not as a caricature, but as a complex, evolving, and strategically central global economy.

References

Andrew Cainey, BUSINESS WITH CHINA: SHOULD I STAY OR SHOULD I GO?, C-Suite Speaker’s Corner, June 2023.

Keyu Jin, The New China Playbook: Beyond Socialism and Capitalism, Viking, 2023.

John Jullens and Marc Robinson, China’s Innovation Ecosystem, C-Suite China Matters, February 2023.

John Jullens and Marc Robinson, Comparative Advantage and Middle-Income Traps: Decoding the US-China Conflict, C-Suite What The Fact, July 2023.

John Jullens and Marc Robinson, Turbulence Ahead: US-China Relations in a Shifting Landscape, C-Suite Trendspotting, September 2023.

The winds of technological and geopolitical change have reached gale force and businesses everywhere must adjust their course or risk sinking. Some changes, such as price adjustments, supply-chain moves, or new marketing approaches, require insight and agility. But others demand major redesigns of processes, strategy, or even business models: genuine transformations that depend on system-wide innovation.

Despite an enormous business literature on innovation and change, the success rate for system innovation remains low. Even well-funded efforts often fade as “programs of the month,” leaving little durable impact. A recent MIT study found that only 5 percent of generative-AI initiatives created measurable value. Avoiding these costly failures requires more than good ideas or smart teams. It calls for a disciplined, organization-wide approach that transcends the mechanics of any single project.

Why System Innovation Fails: The Silo Problem

Innovating systems in large organizations requires that information, decisions, and changes move freely across boundaries. Silos are natural features of scale and specialization, but they also fragment accountability and obscure system-level trade-offs.

The standard prescription is “collaboration,” yet most companies - if they address silos at all - stop at forming a cross-functional team and declaring victory. True collaboration means more than attendance at meetings. It requires the right structure, authority, and incentives so that the team can actually deliver the required change for the organization.

Effective System Innovation Requires Teams, Not Committees

System innovation succeeds only when cross-functional teams are designed and empowered to deliver. Innovation cuts across functions, geographies, and hierarchies, demanding joint decisions, coordinated execution, and unified change management. None of this happens automatically. It requires intentional design, clear accountability, and sustained executive sponsorship.

1. Build a True Cross-Functional Team and Make It Their Primary Job

Many “cross-functional” teams fail because they are part-time efforts layered on top of full workloads. System innovation cannot be done on the side. Executives must explicitly budget time and resources for members to contribute meaningfully. When participation depends on discretionary effort, progress stalls and momentum quickly fades.

2. Give the Project Leader Authority and Organizational Standing

The project leader must have the credibility to work across functions and levels, or report directly to a senior sponsor who does. Too often, the project leader lacks organizational standing and credibility vis-à-vis other functions. Without recognized authority, even routine issues can easily become irresolvable. A senior sponsor or executive steering committee can keep the effort moving and ensure decisions stick.

3. Assign a High-Potential Leader with a Clear Career Incentive

Choose a project leader who has both capability and motivation; ideally a high-potential executive for whom success will be career-defining. Visible advancement opportunities motivate more effectively than short-term bonuses, which seldom correlate with long-term project success. Treat this as a pivotal leadership assignment, not an administrative duty.

4. Make the Team Accountable for Both Design and Implementation

Too many teams disband after delivering recommendations, leaving others to wrestle with the implementation. The same group should stay responsible for early execution to maintain ownership and continuity. Involve implementation leaders early - first as reviewers, later as integrated members - to spot barriers while they can still be addressed.

5. Establish Governance That Enables, Not Delays

Structure matters. Effective governance prevents conflicts from festering and ensures timely decisions. A steering committee should probably meet at least once a month to resolve open conflicts before they linger or escalate. Project management teams typically meet at least once a week to review progress and align workstreams, while individual workstream teams convene as needed to drive execution and learning. This cadence ensures alignment without bureaucracy. The goal isn’t more meetings, but faster learning and faster decisions.

Few Organizations Get All of This Right

Each of these elements may seem obvious, yet rarely are they all implemented on a single project. In more than three decades of system-transformation work, we have rarely seen all disciplines applied together - a key reason system innovation is so difficult, and why those who master it gain lasting advantage.

Organizational Enablers of Lasting Innovation

Even the best-designed cross-functional team will struggle without the right organizational scaffolding. Business anthropologists Briody and Erickson found that collaboration alone was insufficient. Durable success required five reinforcing conditions: leadership buy-in, evidence of benefit, work-process change, work-practice change, and structural change.

1. Leadership Buy-In

Leadership support may seem obvious, but it can be hard to sustain in a siloed organization. Some units will bear more pain than others, and some leaders may believe their areas are already performing well. Effective system leaders demonstrate “lateral agility” - the ability to think and act with an enterprise-wide mindset that reflects multiple functional perspectives.

2. Evidence of Benefit

Change is costly. A system innovation must deliver tangible improvement to earn credibility. Teams should design for measurable early wins - the corporate equivalent of a start-up’s “minimum viable product.” Quick, visible “proof of concept” builds confidence and unlocks further investment.

3. Work-Process Change

Work processes define the idealized flow of work. If underlying processes are not re-designed, people will invariably revert to old habits. Real improvement required incentives that rewarded system optimization instead of local performance.

4. Work-Practice Change

Work practices are the actual day-to-day tasks people perform. System innovation requires changing how that work is done, shifting daily activities to new ways of working so the innovation can become a lasting habit.

5. Structural Change

Large organizations are usually well adapted to today’s business environment. Incentives, roles, and networks reinforce the status quo. Embedding system innovation requires adjusting those structures - not perfectly, but sufficiently - so that the new way of working is easier than the old. With the right support and metrics, people will refine the details themselves.

Leading Change Across the System

System innovation demands sustained vision, determination, and focus from leadership – and disciplined execution from empowered cross-functional teams. It is not easy work, but the payoff is substantial: a durable competitive advantage over less agile incumbents and untested upstarts alike.

In today’s environment of continuous disruption, the organizations that learn to innovate despite the silos will be the ones still standing when the storm subsides.

Elizabeth K. Briody and Ken C. Erickson. “Success despite the Silos: System-Wide Innovation and Collaboration,” In Maryann McCabe, ed., Collaborative Ethnography in Business Environments. London, UK: Taylor & Francis, 2017: 26-59.

Aditya Challapally et.al., “The GenAI Divide: The State of AI in Business 2025,” MIT NANDA Project, 2025.

Welcome to the first issue of our new economic and business roundup. Each month we’ll focus on the top 3-5 forces shaping markets, geopolitics, and corporate decision-making.

1) Is the Trade War Really Winding Down?

The US and China have agreed to a one-year truce in their escalating trade conflict, alongside new framework understandings with Japan, Korea, and Australia as well as exploratory signals toward Brazil and India. At first glance, it may appear that the global trade war is easing. A deeper look suggests otherwise:

• Headline Deal: The US will suspend its “liberation tariffs” of ~24% on Chinese imports for another year in return for China pausing its retaliatory 24% tariffs for the same period. The US Commerce Department will delay its “50% rule” while China will delay export controls on critical minerals and rare earths. The US will also remove 10% tariffs tied to fentanyl enforcement concerns, and both sides will temporarily hold off on countervailing measures in shipping and maritime logistics.

• Reality: Other than fentanyl cooperation, the agreement largely returns both sides to the pre–Liberation Day status quo. Many mechanisms that once managed disputes (e.g., JCCCT) remain dismantled. Crucially, this agreement covers only a narrow set of retaliatory tariffs – i.e., Section 232 investigations are not off the table.

• Risks: Washington retains broad flexibility to escalate through export controls, financial sanctions, and scrutiny of Chinese-listed companies. Beijing would likely view such actions as escalatory and now appears to have genuine leverage over critical minerals and rare earths, a structural advantage it will likely maintain for years.

• Bottom Line: The truce lowers immediate volatility, but strategic rivalry remains fully intact. Expect potential re-escalations and policy volatility in 2026.

2) USMCA: The Next Flashpoint?

With China temporarily stabilized, North America becomes the key trade risk zone.

• Tariff Environment: While headline tariff rates in the U.S. have increased, the real-world impact remains more moderate due to a wide range of exemptions and carve-outs. As a result, the average effective tariff rate is roughly 10%, well below the statutory rate of approximately 18%. The impact is even less in North America; in June, more than 75% of imports from Mexico and Canada entered duty-free under USMCA provisions.

• Policy Uncertainty: Negotiations with Canada and Mexico are expected to resume soon, despite the recent tension sparked by an Ontario ad. A pending Supreme Court challenge could invalidate a portion of current tariffs, though not those on steel, aluminum, autos, or auto parts. Most importantly, the 2026 USMCA review is approaching, and any resulting agreement could introduce meaningful changes to rules and tariff levels.

• Bottom Line: North American supply chains remain highly uncertain and volatile.

3) Government Shutdown: No Obvious Exit Ramp

The federal shutdown shows few natural paths to resolution.

• Political Dynamics: Both sides have framed the dispute in zero-sum terms, making a face-saving deal difficult, despite a logical compromise emerging around extending ACA subsidies with targeted adjustments.

• Battlefield: Republicans aim to pressure Democrats via cuts (e.g., SNAP) and federal workforce strain. Democrats are betting that looming health-care premium spikes shift leverage in their direction.

• Bottom Line: Upcoming elections may shift negotiating incentives. Until then, expect policy paralysis, data disruptions, and delayed federal decision-making.

4) The US Economy: The Calm Before the Storm?

Yes, the Fed did cut rates to 3.75% and halted balance-sheet reduction and markets did respond by pushing major indices to record highs, seemingly confident that the real-economy impact of trade tensions will be modest and that further easing is ahead. Yet structural pressures are building and at least two “Gray Rhinos” are getting ready to charge:

• Tariff Pass-through: Corporate absorption of tariff costs is unsustainable and the first consumer impacts are emerging (e.g., rising auto-loan delinquencies).

• AI Bubble Risk: AI-related investment has been the primary engine of GDP and market activity. If momentum fades, the correction could be sharp.

• Fed Independence Risk: Pressure for aggressive easing will intensify as the next Fed Chair appointment approaches. Short-term rates may fall materially faster than long-term yields once the transition occurs.

• Bottom Line: Wall Street is pricing a “soft landing” but Main Street suggests considerable fragility below the surface.

Key Take-Aways

• Continue to plan for policy volatility, not stability. The US-China truce is unlikely to hold through 2025. Incorporate strategic scenarios, not linear forecasts.

• Build tariff flexibility into contracts. Use explicit tariff pass-through clauses in supplier agreements. Treat Mexico and Canada with heightened caution given USMCA uncertainty.

• Prepare for multiple gray rhinos. Watch for a potential AI-investment correction, renewed trade escalation, monetary policy turbulence and a messy Fed leadership change.

• Strategic Posture. Investment optionality and resilience investments now will pay outsized dividends as volatility returns.

Trump’s criticisms of the Fed aren’t new, but his second-term ambitions do reflect a more assertive stance, as the new administration is actively exploring legal pathways to dismantle the long-standing protections that insulate the Fed from direct political control. At the same time, a shortlist of potential successors to Powell is emerging, with some candidates already signaling their willingness to align monetary policy more closely with the White House’s growth agenda.

New Business Risks

Trump has explicitly argued that lowering interest rates would help reduce the federal deficit, a view rooted in the assumption that lower debt servicing costs will ease budget pressures. Historically, however, this line of thinking has proven risky. The only time the Fed explicitly held rates low to reduce government interest costs was immediately after WWII. The result was a sharp rise in inflation in the late 1940s, ultimately leading to the landmark 1951 Treasury-Fed Accord that re-established the central bank’s independence and shifted its focus to price stability. This episode remains a foundational moment in the Fed's institutional history.

The implications of a less autonomous Fed extend far beyond interest rates alone, as financial markets depend on the Fed’s credibility to function smoothly. If investors begin to doubt the central bank’s independence, the ripple effects could be profound. Bond markets may react with volatility, pushing yields higher in anticipation of inflationary pressures. And it’s important to remember that, while the Fed controls short-term rates, markets dictate long-term ones. If the Fed is seen as sacrificing its inflation target, long-term rates may actually rise, undermining the very deficit-reduction goals that the administration is pursuing. With the majority of U.S. government debt issued at longer maturities, this could backfire, leading to higher federal interest payments.

Foreign investors, who currently hold roughly one-third of all U.S. Treasury debt, could demand risk premiums or reduce their exposure altogether, raising borrowing costs and tightening financial conditions across the board. But the impact won’t be limited to yields alone. If inflation expectations become unanchored, the dollar may fall, and risk premiums for U.S. assets may rise as markets begin pricing in broader concerns about economic mismanagement and institutional erosion. While the risk of an outright U.S. default is more tied to fiscal dynamics than monetary policy, a perception that the Fed is “printing money” to monetize deficits could reinforce those fears.

And the consequences of Fed politicization wouldn’t be confined to U.S. markets alone. Emerging economies, many of which carry large amounts of dollar-denominated debt, would be especially vulnerable. Currency volatility could increase refinancing costs, lead to capital flight, and in some cases trigger sovereign debt crises. These effects would likely cascade through global supply chains, particularly in sectors dependent on trade finance, such as manufacturing, pharmaceuticals, and energy.

The dollar’s role as the world’s reserve currency could also come under scrutiny as any erosion of trust in the Fed’s capacity to act independently in a crisis could accelerate moves by sovereign wealth funds and central banks to diversify reserves into alternative currencies or assets. Such a development would mark a significant shift in global economic power and create heightened uncertainty for multinational firms that operate across borders or rely heavily on dollar-based trade. In fact, some central banks have already been increasing their gold reserves in anticipation of greater geopolitical and monetary fragmentation.

The U.K.’s recent experience provides a cautionary tale. In 2022, then-Prime Minister Liz Truss unveiled a budget packed with unfunded tax cuts that triggered a sharp sell-off in bonds and the pound. The resulting market turmoil was so severe that it forced her resignation after just 45 days, famously failing to outlast a head of lettuce in a viral tabloid stunt.

At the same time, we should avoid slipping into apocalyptic thinking. From 2008 to 2013, some monetarists loudly warned that deficits and near-zero interest rates would unleash runaway inflation. It didn’t happen. In fact, the policy may have been too timid. Even if a Trump-appointed Fed Chair were to slash rates by a few points, the outcome may not be catastrophic. As the 2021 inflation spike showed, inflation, even at uncomfortable levels, does not necessarily cripple economic performance and can even produce strong nominal growth and corporate earnings. However, it does generate intense political pressure for stabilization, which in turn constrains policymakers.

That’s why the real risk here is less about any one decision and more about erosion over time. A politicized Fed may not trigger an immediate crisis. But it could gradually undermine market confidence, institutional credibility, and global economic leadership, much as we’ve already seen with the weakening of multilateral trade institutions.

C-Suite Implications

For C-Suite executives, it may be tempting to dismiss all this as merely a political issue, but the business implications are simply too large and plausible to ignore. This isn’t about sounding alarms but about developing organizational resilience while there’s still time. The risk of Fed politicization must be incorporated into enterprise-level strategy and capital planning, not merely as a tail-risk scenario, but as a plausible feature of the economic landscape in the next 12 months and beyond.

Start with capital structure. Companies should prepare for a wider range of interest rate outcomes, including abrupt policy shifts that may not align with macro fundamentals. This means evaluating the flexibility of existing debt arrangements, assessing the timing of new issuance, and building liquidity buffers to navigate periods of rate instability. Inflation preparedness must also be rethought. Traditional approaches such as cost-cutting and procurement optimization are not enough. Leaders should consider geographic diversification of supply chains, renegotiation of supplier contracts to include inflation-linked clauses, and accelerated automation to reduce wage exposure in tight labor markets. Currency risk is another critical area. Businesses with significant overseas revenue or import costs denominated in dollars should explore hedging strategies and alternative reserve structures. In some cases, it may even make sense to hold a portion of corporate liquidity in non-dollar assets, such as euros or gold, particularly if counterparties begin doing the same.

Lastly, strategic planning processes can no longer treat Fed credibility as a given. Boards and executive committees should stress-test against a world in which inflation expectations are unanchored, foreign capital becomes more selective, and monetary policy reacts to political cycles rather than economic signals. To be clear, this isn’t about predicting political outcomes but about ensuring organizational resilience in a changing business environment where traditional institutional norms are no longer a given.

Given the stakes, CFOs in particular cannot afford to remain passive observers. The moment to act is now to ensure their organizations aren’t surprised by what could very well be the next Gray Rhino – a highly visible, high-probability risk that too many still fail to prepare for.

Sources

“The real reason Trump wants to fire the Fed Chair,” Brainard, Washington Post (July 2025)

“Fed Independence: How Concerning?”, Goldman Sachs (2025)

“Can a Footnote Save the Fed?”, Eichengreen, Project Syndicate (May 2025)

“The Apprentice: Federal Reserve Edition”, Rogoff, Project Syndicate (May 2025)

“Financial Stability Requires an Independent Fed”, Johnson & Liikanen, Project Syndicate (May 2025)

“What if Trump Subdues the Fed?”, Eijffinger & Mujagic, Project Syndicate (Dec 2024)

It’s remarkable that only a decade ago, the Chairman of a major Chinese state-owned automaker warned that “Chinese manufacturing presently faces the biggest crisis in its history.” At the time, China’s automakers were still struggling to catch up with their far more experienced and capable rivals from the West and Japan. Today, the script has flipped. Chinese brands are challenging the automotive world order, especially in the EV sector, where the question is no longer if Chinese firms can compete but whether legacy automakers in the U.S. and elsewhere are ready.

A Decade Ago: The Inflection Point

In 2014, China’s automotive industry was nearing a structural inflection point. Growth had slowed from an explosive 25% CAGR to a more GDP-aligned 6% range, while the product lifecycle (number of vehicles produced) and industry lifecycle (number of independent automakers) were beginning to decouple. As a result, overcapacity was rising - along with mounting pressure on margins and costs - and competitive dynamics were shifting.

At the same time, demand was bifurcating between Tier 1 and lower-tier cities. In higher-tier cities, saturation and wealth effects led to slower growth and a shift toward premium and replacement vehicles. In contrast, lower-tier cities saw continued growth from first-time buyers. Regional fragmentation in consumer preferences, combined with a shift from compact cars to SUVs, suggested the need for dual business models and multi-brand portfolios. Success would require stronger regional marketing and sales capabilities.

As the market matured, profit pools began to shift. Used vehicles from higher-tier cities started cannibalizing new vehicle demand in lower-tier regions. The aftermarket was emerging as a critical source of profitability, though its most lucrative segments risked being captured by independent players and global suppliers. Increasingly, lease and finance products were becoming essential sales enablers, especially for younger consumers.

Altogether, the business model was evolving from a “hunter-gatherer” paradigm focused solely on new car sales to a “seed-harvest” model. In this new context, capabilities such as cross-selling, used vehicle management, and aftermarket service and parts became essential. Retailers and dealers, in turn, would require far more robust OEM support.

Perhaps the most radical notion at the time was that some Chinese automakers could become global category killers following a five-stage process: gain domestic dominance, leverage cost advantages, drive innovation through relentless cost focus, expand internationally, and move up-market via R&D and strategic partnerships. To many industry executives, this sounded fanciful. A decade later, it’s clear that’s exactly what has happened.

From Doubt to Dominance: The Rise of BYD

By 2025, several Chinese automakers, most notably BYD, have indeed emerged as formidable global competitors. Originally a battery maker, BYD has become the world’s leading EV manufacturer. A 2023 UBS teardown of the BYD Seal - a sleek, high-performance sedan - revealed not only a vehicle superior in build quality to its Western rivals but also up to 25% cheaper to produce.

BYD’s growing portfolio includes budget-friendly models such as the Seagull (under $12,000) and Dolphin, as well as larger electric SUVs like the Song and Tang. These models deliver a compelling mix of value, design, and performance - qualities that are resonating well beyond China’s borders.

To support its global ambitions, BYD is aggressively localizing supply chains, manufacturing, and talent. Its four existing overseas knock-down (KD) plants each exceed 40% localization rates. New facilities in India, Turkey, and Mexico are expected to surpass that benchmark.

However, caveats remain. BYD’s core strengths - agility, vertical integration, and risk tolerance - are deeply embedded in China’s business ecosystem. Whether these advantages will translate abroad remains uncertain. Challenges around brand management, regulatory hurdles, and geopolitical tensions could all slow the company’s advance. And then there are questions regarding the firm’s financial health, including speculation that it might even be the next Evergrande. Still, the parallels with the rise of Japanese automakers in the 1980s are striking: a new competitor, operating on a different productivity frontier, is resetting global expectations.

Strategic Thresholds: Will the Threat Materialize?

Whether Chinese EV manufacturers represent an existential threat to U.S. legacy automakers hinges on two key variables: the pace of EV adoption in the U.S. and the degree of market access available to Chinese firms.

EV Uptake and the Adoption Chasm

The U.S. EV market is currently experiencing a familiar phenomenon in technology adoption: the “chasm” between early adopters and the early majority. Sales have slowed as the latter group - who prioritize cost, convenience, and reliability - remains unconvinced. These adoption “saddles” are common, often lasting several years and delaying mass-market penetration. It remains to be seen whether EVs will fully replace internal combustion engine (ICE) vehicles, or whether the market will segment into a mix of powertrains based on region, duty cycle, and use case.

Market Access: The New Gatekeeper

At the same time, Chinese automakers face significant headwinds in entering the U.S. market. From tariffs to national security concerns, the political environment is increasingly adversarial. Yet Chinese OEMs are not standing still. Mexico is emerging as a strategic beachhead.

By leveraging USMCA trade protections, Chinese automakers are building capacity in Mexico to potentially target under-served white space at the bottom end of the U.S. market, namely ICE passenger cars and trucks priced below $30,000. This strategy allows them to build local credibility, scale operations, and establish cost advantages before launching a full EV offensive when market conditions permit.

In this context, Mexico may become the Omaha Beach - only in reverse - for U.S. legacy automakers: the critical point of Chinese market entry for a much larger strategic incursion.

Four Strategic Futures: Scenarios for 2035

Plotting EV adoption against Chinese market access yields four plausible future scenarios:

1. ICE Fortress (Low EV Uptake, Low China Access)
   EV policy rolls back. Chinese OEMs are blocked. The D3 double down on ICE and hybrids but risk falling behind globally.

2. EV Divide (High EV Uptake, Low China Access)
   Coastal markets go electric. Interior markets lag. Chinese firms are kept out, but the D3 face intense competition from Tesla and European brands.

3. Danger Ahead (Low EV Uptake, High China Access)
   Chinese OEMs gain entry via Mexico and Latin America, starting with ICE and hybrids. U.S. firms are caught off guard.

4. Wipe-Out (High EV Uptake, High China Access)
   The existential scenario. Chinese EVs enter at scale, outcompete on cost and tech, and overwhelm unprepared U.S. incumbents.

Strategic Postures: How the D3 Can Defend

U.S. automakers must first ask: are Chinese advantages - vertical integration, speed, digital ecosystems - replicable abroad, or context-specific? If not easily transferable, opportunities exist to slow or neutralize the threat.

Key strategies include leveling the playing field through local sourcing mandates, supply chain requirements, and regulatory alignment and/or exploring joint ventures, akin to the 50:50 JVs China itself once required, to control critical assets like distribution, areas where Chinese OEMs are weakest. Export restrictions should probably be avoided as they merely delay instead of solving competitive deficiencies.

Meanwhile, the competitive landscape in China is shifting fast. Should Chinese OEMs consolidate through friendly M&A over the next 3–4 years, they will likely accelerate global expansion. Early collaborations - e.g., VW with XPeng or Nissan with Dongfeng - suggest a potentially viable “In China for Global” model that may offer U.S. firms a fast-track to innovation and scale, if they’re willing to engage.

The Road Ahead: A Ticking Clock

Chinese EV makers are not yet dominant in the U.S., but the threat is no longer theoretical. With the right combination of consumer tailwinds, policy changes, and supply chain momentum, they could trigger an industry-wide upheaval.

The imperative for U.S. automakers is clear: don’t wait. Anticipate. Test scenarios. Partner smartly. Most of all, defend North American ground - especially in Mexico - decisively and early.

The next chapter of the automotive industry is being written now. The question isn’t whether Chinese EVs will come. It’s whether the U.S. auto industry will be ready when they do.

Sources

“How Did China Leapfrog Everyone in EVs?” Jullens and Robinson, ww.csuitenewsletter.com, 11 August 2023

“How Emerging Giants Can Take on the World,” Jullens, Harvard Business Review, December 2013

Jullens, “Extended China Board Meeting” presentation for a global automotive supplier, Shanghai, 18 April 2014

“The Electric Vehicle Slowdown: A Lesson in Technology Diffusion and Saddle Patterns,” Jullens and Robinson, www.csuitenewsletter.com, 24 August 2024

“Turbulence Ahead: US-China Relations in a Shifting Landscape,” Jullens and Robinson, www.csuitenewsletter.com, 14 September 2023

Will Chinese Electric Vehicles (EVs) win globally?” UBS, 7 Sep 2023

On April 9, when China responded to new U.S. tariffs with export restrictions on rare-earths, few observers seemed overly concerned. But as the days turned into weeks, companies across the automotive, electronics, and defense industries began scrambling. Shipments were delayed. Supplies dried up. And C-Suite executives, who may have paid little attention to rare-earths before, were suddenly treating them like oxygen: invisible maybe, but also absolutely essential.

Rare-earth magnets are critical to the functioning of modern economies. They are found in a wide range of products, including electric motors, wind turbines, smartphones, and fighter jets. They are also, despite their name, commonly found in the earth’s crust. The problem isn’t scarcity, it is control. Why? China currently dominates the global supply chain with 70% of the world’s rare-earth mining and about 90% of its refining capacity - and it hasn’t hesitated to weaponize that control. The result is a geopolitical standoff with consequences that could easily eclipse the 2021 chip shortage or the post-tsunami collapse of Japanese auto exports. As Ford CEO Jim Farley recently put it in an interview with Bloomberg, “We have had to shut down factories. It’s hand-to-mouth right now.”

It Ain’t Over Until It’s Over

Despite headlines about a truce, the rare-earth crisis is far from over. On paper, both governments have agreed to a temporary easing: China will issue six-month export licenses for automotive companies, and tariffs will revert to the 55% level set earlier in the Trump 47 administration. But the devil is in the permits, as Chinese authorities continue to control magnet and rare-earth exports through a meticulous licensing process. Each shipment must include details about its final destination and use. So far, the approvals are trickling in far too slowly to restore confidence, let alone inventories. And, as it plays cat-and-mouse with approvals, Beijing is gaining unprecedented visibility into global supply chains.

What makes rare-earths such an effective weapon is that the pain they cause is rapid and precise, while the costs to China itself remain minimal. As inventories deplete, manufacturing lines outside of China grind to a halt. Tariff threats and visa bans may generate headlines, but they’re no match for the invisible chokehold of rare-earth dependence.

The Rare Earth Game

Importantly, this crisis wasn’t exactly a surprise. It was a long-anticipated move in a strategic game that China has been playing, and winning, for over two decades. Beijing recognized long ago that control over critical raw materials would translate into geopolitical leverage. It systematically built dominance in refining and rare-earth production while Western governments, wary of environmental backlash and confident in global markets, let their own capacity atrophy.

The first time China used its rare-earth leverage was in 2010, during a territorial dispute with Japan. The two-month export ban crippled Japanese automakers and prompted Tokyo to take action. In partnership with industry, the Japanese government secured long-term supplies from an Australian mine and a Malaysian refiner. To be clear, the U.S. did try its own version, removing regulatory barriers to reopen a rare-earth mine in Utah. But the effort failed, in part because the refining still took place in China. When China subsequently flooded the market, prices collapsed, and the mine shut down again. The lesson? Without full supply chain integration, and the political will and customer commitment to support it, independent rare-earth strategies are doomed to fail.

Today, China continues to tighten its grip. It has consolidated domestic producers, cracked down on illegal mining, and inserted itself into foreign supply chains through refining partnerships. With export licenses now contingent on end-use disclosure, the Chinese government effectively holds the throttle on global production. Whether over Taiwan, the South China Sea, or future tariffs, rare-earths are now a go-to tool in China’s geopolitical playbook. For business leaders, the message is clear: assume this crisis will repeat and plan accordingly.

What Now?

In the short term, companies must treat the current crisis as both a fire to put out and a fire drill for the next one. Here’s where to start:

1. Institutionalize Workarounds
   During the blockade, firms resorted to improvisation: recycling magnets, downgrading trim levels, rerouting motors for assembly inside China. These contingency measures should be documented, analyzed, and refined, not just forgotten when the crisis ebbs again.
   => Every workaround represents a proof-of-concept for a more resilient operating model.

2. Secure Alternative Supply
   Non-Chinese suppliers, such as the Malaysian refiner, have proven resilient. Now is the time to seek or expand long-term contracts. Explore their capacity. Offer investment. Treat them like strategic partners, not just vendors.
   => Securing non-Chinese supply is no longer about optional diversification but about operational sovereignty.

3. Elevate Crisis Management
   At the first sign of disruption, a cross-functional team with a“war room” should be activated under a single accountable leader. Members must have decision-making authority and crisis temperament. Data must flow continuously. And supplier relationships should be strong enough to enable collaboration, not finger-pointing, under pressure.
   => Speed, authority, and trust, not just contingency plans, determine who gets back online first.

4. Scenario Planning and Wargaming
   Treat rare-earths like a battlefield. Develop scenarios ranging from a short-term trickle to a long-term freeze. Run pre-mortems and other stress tests. Identify weak links. Apply the lessons to other critical materials where China also dominates, such as graphite and cobalt.
   => Today’s weak point is rare-earths. Tomorrow’s may be graphite.

Breaking the Cycle

Longer term, the only solution is to reduce dependence on China. The U.S. government’s past efforts offer a cautionary tale: narrowly focused on mining only, bureaucratically hobbled, and fatally underfunded. The private sector cannot fix this alone, as even giants, such as GM and Ford, lack the scale to shift the rare-earth landscape. What’s needed is a joint, coordinated effort across firms, sectors, and borders.

This is where the G7 must step in. Just as “Operation Warp Speed” mobilized public and private resources during the pandemic, a similarly ambitious initiative is required to rebuild a rare-earth supply chain outside China. That means not just mining, but refining, production, and research into rare-earth alternatives. The G7 can also learn from Japan, working with companies to develop independent supply chains and sustain them for the long term, even at modest short-term losses compared to buying from China. And it must be resilient to counterattacks. As new capacity comes online, China will likely flood the market again to drive down prices and undermine confidence. Beyond the G7, partnerships with emerging producers in other countries, such as Australia, India, and select African nations, will be essential to building a truly global counterweight to China’s mineral dominance.

The Bigger Game

The clean energy transition has fueled the global race for critical minerals, transforming rare-earths and other elements, including lithium, manganese, and cobalt, into strategic assets. At the center of this emerging resource war is the escalating rivalry between China and the United States for next-generation technological supremacy.

China currently dominates the global supply of rare-earths. Importantly, its dominance stems not just from geological luck, but from decades of strategic industrial policy and targeted investment. In contrast, the U.S. remains fully import dependent for rare-earths and 14 critical minerals and more than 50% dependent for another 34. This poses a strategic threat to key sectors, including automotive, semiconductors, defense, and clean energy. It also leaves the U.S. vulnerable to geopolitical pressure in ways that many executives are only now beginning to understand.

The scramble for critical minerals is also reshaping global alliances. Resource-rich developing nations, especially in Africa and Central Asia, are increasingly courted by both Washington and Beijing. In fact, much of China’s activity in these regions is defensive and about pre-emptively locking in independent sources of supply for the next phase of the technology war. The United States still retains a dominant position in global finance, but China holds the upper hand in rare-earths, and, increasingly, in the industrial supply chains that matter most.

Even if the world does succeed in building a rare-earth alternative, the game won’t end there. China also dominates in graphite, lithium, and cobalt, each critical to advanced batteries and the energy transition. In other words, the rare-earth crisis is merely the opening chapter in a broader story. For C-Suite executives, this moment demands a shift from reactive to strategic, as survival won’t just go to the best player; it’ll go to the one who rewrites the rules.