The Expertise Deficit
Why Not Knowing Has Become Acceptable
A corrosive pathology has taken hold over the past decade: not just the erosion of expertise, but a growing visceral dislike and distrust of experts themselves. In some circles, not knowing has become a badge of honor. How did this happen? And what does it actually cost business and governmental organizations?
How Did We Get Here?
The current anti-expertise sentiment is the predictable result of at least four converging forces.
1) The Great Disappointment of Neoliberalism. Codified in the Washington Consensus and launched by the Reagan/Thatcher revolution of the 1980s, a neoliberal policy agenda took hold across the Western world: deregulate markets, shrink government, liberalize trade, and trust markets over governments to deliver broad prosperity. The collapse of the Soviet Union seemed to settle the argument permanently. The economists, policy advisors, and international institutions who championed the neoliberal agenda were unambiguous in their predictions: rising tides, they insisted, would lift all boats. What actually materialized, however, was dramatically increasing inequality with the share of income going to the top 1% in the US surpassing even the Robber Barons of the Gilded Age. When experts have been so spectacularly wrong about something so consequential, it is not entirely irrational to question their authority.
2) The Collapse of a Shared Information Commons. For most of the twentieth century, a relatively small number of authoritative sources, most notably Walter Cronkite and the CBS Evening News, shaped a shared set of facts held by most citizens. The internet destroyed that model. Today we are awash in an unmediated torrent of information in which expert opinion, amateur speculation, and deliberate disinformation are indistinguishable. The packaging is identical. People self-select into algorithmic echo chambers that reinforce what they already believe. In this environment, expertise becomes just one more competing voice.
3) The Credibility Crisis in Institutions. Trust in virtually every major institution has fallen to historic lows, and some of that distrust is earned. Financial institutions that caused the 2008 crisis were bailed out while millions of ordinary citizens lost their homes and savings. Political dysfunction and visible incompetence have made governance seem like a performance rather than a function. And the collapse of replication in academic research has revealed that many landmark findings, including some that shaped public policy, simply don’t hold up. When institutions that are supposed to embody expertise fail so visibly and repeatedly, the logical inference is that the experts running them don’t really know what they’re doing.
4) COVID: The Right Lesson Is Not the Obvious One. The COVID-19 pandemic is frequently cited as Exhibit A that experts cannot be trusted. This is both understandable and wrong. The problem was not that the true experts failed. Virologists and epidemiologists such as Christian Drosten (Charité, Berlin) and Michael Osterholm (University of Minnesota) were consistently insightful and prescient. The problem was that the pandemic created a vast stage for impostors. Economists, physicists, tech entrepreneurs, and even family practitioners far outside their clinical lane claimed epidemiological authority they did not possess. The correct lesson from COVID is not that expertise failed, but that non-experts lack the tools to distinguish real expertise from self-declared expertise.
Together, these forces have created an environment in which skepticism of expertise has become not just common but normalized. And the same cultural forces that eroded public trust in expertise did not miraculously stop at the corporate door. Executives who built their careers during the neoliberal era absorbed its core belief in the power of markets and incentives, whereas those who came of age in the internet age absorbed the related belief that data, dashboards, and AI-assisted tools are adequate substitutes for the deep domain expertise previous generations had to develop the hard way. Neither assumption is entirely wrong but, taken too far, both are dangerous. As a result, inside many organizations there is a silent but significant degradation of standards: for what counts as genuine capability, for what level of expertise is required for making high-commitment decisions, and for what it actually means to know something as opposed to merely having access to information about it.
That environment is made worse, and more difficult to escape, by what psychologists call the Dunning-Kruger effect: people with low competence in a domain not only systematically overestimate their own ability but also lack the metacognitive awareness to recognize their deficiency. Ignorance, in other words, is invisible to itself.
The Dunning-Kruger effect is not merely an individual psychological phenomenon. It is the primary reason organizations fail to self-correct on capability gaps, and its implications grow more dangerous with seniority. A mid-level analyst who overestimates their competence may produce a flawed model, but a senior executive who overestimates their strategic judgment may lock the organization into a flawed strategy with no internal mechanism for correction. The gap between perceived and actual expertise is where poor decisions live.
The Cost of Not Knowing is Measurable
Of course expertise matters. We don’t question whether plumbers should know something about pipes or whether dentists should understand teeth. The same logic should apply, with even higher stakes, to the organizations that shape our economies and govern our lives. And yet, increasingly, it does not – not at the national level, not at the organizational level, and not at the functional level.
Brexit: The Definitive Field Experiment. Brexit represents a rare “live” economics experiment at national scale. When Michael Gove, a senior cabinet minister and one of the Leave campaign’s chief strategists, declared that “people in this country have had enough of experts,” he was explicitly dismissing the overwhelming consensus of economists, political scientists, trade experts, and international relations scholars who predicted that leaving the European Union would do substantial harm to the British economy. Nearly a decade later, the verdict is in: the experts were right. The UK has underperformed comparable economies, trade friction has increased, financial services have migrated to continental Europe, and growth has lagged. The costs of dismissing expertise are being borne by millions of ordinary British citizens, most of whom are now bearing costs they did not anticipate and cannot easily reverse.
Boeing: When Engineering Culture Erodes. The same dynamic operates at the organizational level. Boeing’s 737 MAX disasters did not emerge from a single catastrophic failure but from a cultural erosion over roughly two decades. Engineers who had previously held ultimate authority over safety decisions were progressively outranked by program managers focused on schedule and cost. By the time the MAX was in development, the culture had normalized shortcuts that an earlier Boeing would not have tolerated. The spreadsheet, it turned out, was not running the numbers correctly either.
The Marketing Capability Gap. The same dynamic plays out at the functional level. A 2023 Ipsos study of 1,226 marketing practitioners found that only 35% met a basic benchmark of foundational marketing knowledge (covering concepts such as brand positioning, media planning, and market share dynamics) even though the vast majority expressed high levels of confidence in their own abilities. Moreover, the weakest areas were precisely the ones that matter most for long-term brand growth: understanding how advertising investment links to market share, and what it actually means to build mental availability. The study also found that formally trained marketers are four times more likely to meet the benchmark than those who learned purely on the job, and that training is a far stronger predictor of capability than seniority, specialization, or years of experience. Experienced people who don’t know the fundamentals are, it turns out, confidently wrong in ways that matter commercially. This is Dunning-Kruger at scale.
The pattern is consistent across levels of analysis - national, organizational, and functional. Survey after survey of senior leaders finds the same pattern: nearly universal acknowledgment that capability building is urgent, paired with near-universal doubt that it has actually been achieved. Awareness of a capability gap and the will to close it are not the same thing. Most organizations have the first. Far fewer sustain the second. The deficit of genuine expertise creates measurable costs at every level. It shows up in poor decisions, slow execution, misallocated resources, and strategies that never translate into outcomes.
Expertise as Strategy
The diagnosis points directly to the prescription. If functional capability gaps are the organizational expression of a broader cultural devaluation of expertise, then closing them requires not just operational fixes but also a deliberate decision, at the leadership level, to treat genuine expertise as a strategic asset and to build the organizational structures that develop, protect, and reward it accordingly.
The operational foundations remain essential: build core capabilities deliberately rather than assuming they will accumulate through experience. Hire and train for genuine depth, not just credential signals. Provide enabling infrastructure, including tools, systems, and decision support, that allows expertise to be applied effectively. Incentivize and reward mastery rather than confident presentation. But these are the floor, not the ceiling. The hard part is what comes next.
Expertise for a Non-Linear World
The expertise that was decisive in a stable, slow-moving competitive environment is not the expertise that will be decisive now. Strategic foresight, the ability to think systematically about alternative futures and their implications, is undervalued and underdeveloped in most organizations. So is the capacity for high-quality decision-making under genuine uncertainty, where the probability distribution itself is unknown, not merely the outcome. Most organizations have learned to manage modeled risk. Far fewer have built any capability for navigating genuine uncertainty.
The distinction matters practically. Shell’s scenario planning unit, built in the 1970s and sustained across leadership transitions and market cycles, allowed it to anticipate both the 1973 oil shock and the collapse of oil prices in the 1980s while competitors were still reacting. Similarly, scenario analysis allowed a small number of financial institutions to anticipate the 2008 mortgage crisis while peers remained fully exposed, not because they had superior data, but because they had analysts with enough domain depth to question what the models were assuming. In both cases the advantage was not more information but the expertise to interpret the data correctly under conditions where most others could not.
Can AI Fill the Expertise Gap?
There is a tempting narrative in which AI compensates for human expertise deficits. This narrative is dangerous. Without genuine expertise in the humans directing it, evaluating its outputs, and making the final calls, AI produces confident-sounding answers to poorly framed questions. Knowing what a concept means, how a mechanism works, or why a methodology matters determines whether AI outputs are accepted at face value or examined with commercial discipline. The organizations that will benefit most from AI are those with the deepest human expertise to direct it.
Depth by Design Instead of Default
In complex, fast-changing environments, generalists who can synthesize across domains often outperform specialists who cannot see beyond them. The resolution is a portfolio answer, not a universal one: foundational literacy is non-negotiable for anyone in the relevant domain; deep specialization is context-dependent and should be calibrated against strategic need. The Capability Investment Audit provides the structure for making that distinction rigorously rather than by default.
The Capability Investment Audit
The most useful practical tool for C-Suite leaders is a Capability Investment Audit: a structured, honest assessment of where expertise actually lives in the organization, whether it matches strategic priorities, and where the critical gaps are. It is, at its core, a modern version of the classic make-vs-buy decision, applied to capabilities rather than physical products and components. The logic is identical: build what differentiates you, source what others can do better or more efficiently, and be rigorous about which is which.
The audit is organized around three questions and two dimensions, each designed to force the kind of clarity most organizations avoid.
The three questions: Which capabilities drive differentiated competitive performance; the ones that, if lost, would directly compromise your strategic position? Which capabilities are table-stakes, necessary but not differentiating, required to play but not to win? And which capabilities are genuinely best sourced externally, where the external market provides superior depth, speed, or flexibility that internal investment cannot match?
The two dimensions: depth of current capability and strategic criticality or how central is this capability to the value proposition, now and in the future that is emerging? Mapped against each other, these two dimensions produce a simple but powerful portfolio view of organizational capability.
The resulting capability portfolio map requires active allocation decisions. Capabilities that are both differentiating and currently shallow require urgent, sustained investment; table-stakes capabilities can be managed for efficiency. Capabilities that are genuinely best sourced externally should be managed with a different discipline: the ability to evaluate, direct, and integrate outside expertise. That ability, to be an intelligent buyer and integrator of external knowledge, is itself a capability that must be built deliberately. As with physical make-vs-buy decisions, outsourcing a capability you don’t understand is a path to dependency and eventual strategic vulnerability.
The Expert and the Bathwater
The anti-expertise sentiment that has taken hold in public culture is, at some level, understandable. The experts of recent decades have given people genuine reasons for skepticism. The COVID pandemic made the pattern visible at global scale: self-described expertise proliferates fastest precisely when genuine expertise is most needed.
The question for every C-Suite leader is not whether expertise matters. The evidence on that is unambiguous. The question is whether you are building it deliberately enough, in the right places, to matter when it counts.