Learning from the History of Technological Revolutions
Trendspotting 1 - Special Issue on AI and Digital Transformation
There can be little doubt that a cluster of emerging digital technologies - including the Internet of Things, digital platforms, blockchain, and especially AI – will fundamentally change how we live, where we work, and potentially even humanity itself. What isn’t so clear is precisely how this process will play out and over what time frame. Will there be a rapid technological convergence and highly disruptive revolution over a relatively short period of time or will technological diffusion evolve sequentially at a much slower rate with far less disruption to business and society? Will the process play out similarly across all industry sectors, markets, and geographies or will there be significant divergence? How will the actions of regulators positively or negatively affect this process? And what organizational changes do C-Suite executives need to make to help their organizations better position themselves for future success?
To help answer these questions, Zlatko Bodrožić from the University of Leeds and Paul Adler from the University of Southern California have developed a powerful conceptual framework1, based on the five great technological revolutions of the last two centuries: the original Industrial Revolution, Steam-and-Railroad Age, Electricity-and-Steel Age, Oil-and Automobile Age, and Information-and-Communication.
Bodrožić and Adler’s have identified common patterns in how organizations and governments responded to the challenges posed by these new technologies. Specifically, they identify four potential scenarios for how the coming digital transformation may unfold, based on based on different potential organizational and public-policy responses.
Given the inherent complexity of Bodrožić and Adler’s model and scenarios, we will address them in two articles. This initial article looks at the patterns of technological revolutions and their implications for business, while a future companion article will look at the four scenarios and their impact on decision-makers.
The importance of technological revolutions
Dating back at least to Schumpeter2, economists have recognized technological revolutions as central to the success of capitalism. Firms compete on technologies, with successful innovators inspiring imitators. Innovations spur a tsunami of complementary advances. For a revolution to occur, the core technology must have applications across many industries. Such revolutions have transformed not just individual industries but whole societies.
Patterns in four technological revolutions
Four distinct – though overlapping – technological revolutions occurred in the two centuries before World War II. The first, called the Industrial Revolution, was based on water power and machinery. It was followed by three so-called “Ages”: steam and railways; steel, electricity and heavy engineering; and oil, automobiles and mass production. Each of these revolutions began in one or two countries (eg, the US and Germany for electricity and steel), and adapted to local conditions as they spread. Each started with a broadly applicable technology (eg, electricity), key commodity inputs (eg, iron), and a core industry (eg, steel). Each emerging technology was expanded by supporting infrastructure (eg, intercontinental trade on steel ships), complementary technologies (eg, heavy engineering), new production processes (eg, flexible production based on electric motors), and eventually by unanticipated new applications (eg, the telephone).
The four technological revolutions had more in common than clusters of technologies and enablers – they also went through similar phases:
Incubation, during which the core technology emerges
Installation, as investors pile in to support the rapid expansion of the technology, with the development of complementary products, processes and infrastructure
Crisis, when new tensions associated with the investment frenzy generate economic and social upheavals
Wide deployment, as the private and public sectors adopt, and adapt to, the innovations
Exhaustion, when the revolution is over and direction of technological innovation shifts.
The interaction of technology, organizations and public policy in a technological revolution is a key insight. In each case, the new technology led to a new organizational paradigm. “Each new paradigm emerged in two problem-solving cycles, with each cycle yielding a new dominant management model”.3 The first cycle resulted in a new management model to suit the technology, since even organizations and processes well-adapted to earlier technologies are not flexible enough to maximize the benefits of the new cluster of technologies. But these new, efficient management models often generated conflict, requiring a second cycle to balance the model with a less top-down approach. For example, the Age of Steel and Electricity allowed faster throughputs and more efficient factory layout. “Scientific Management” became the new model, characterized by time-and-motion studies; but this also generated dysfunctions such as highly regimented routines that alienated workers. This triggered a second cycle of organizational innovations that focused on mitigating these dysfunctions. A “factory” paradigm became dominant, combining Scientific Management with individualized supervisor-employee relations.
During technological revolutions, public policy has undergone similar cycles. In the installation phase, excitement over new technologies has led governments to remove barriers to growth, adopting a laissez-faire approach that resulted in massive, dominant new firms. The subsequent crisis phase caused governments to try to check oligopolistic excesses and spur wider deployment of the new technologies. In the Age of Steel and Electricity, the laissez-faire Gilded Age gave way to the Progressive Era, in which governments strove to address inequality, social ills and economic panics.
Information and Communications Technology Revolution
Information and communications technology (ICT) is the most recent technological revolution, though its incubation phase dates to the 1940s. Though it is still underway, the common pattern is already evident. A new, broadly applicable technology (computers and transistors) and new core inputs (digital data) created a new technological paradigm. This paradigm was augmented by new supporting infrastructure (the internet), complementary technologies (telecommunications), and computer-controlled production processes. New applications emerged, such as smartphones and their apps.
The ICT revolution has gone through its incubation and installation phases. During the installation phase, there was considerable frustration about the limited practical economic value of computers. Robert Solow famously said, “you see computers everywhere but in the productivity statistics.” One hold-up was the difficulty of redesigning and automating business processes; a second was barriers to sharing data. Data barriers dropped with the emergence of the internet, broadband, and cellular networks.
Organizational structures adapted as well, albeit unevenly. Bodrožić and Adler call attention to the Business Process management model that has broken down silos within organizations and connected supply chains. But we believe they have undervalued the organizational innovations of start-up culture and of digital platforms [tied to warehouse/delivery networks (like Amazon) or distributed services (like AirBnB or Uber)]. Public policy has been largely laissez-faire in the US, while Europe has pushed privacy and antitrust regulations, and autocratic governments have tried to both control and exploit ICT.
Bodrožić and Adler think that the deployment phase is about to begin, but - with computers in everyone’s pocket providing access to much of the world’s knowledge, and the ability to buy almost anything from anywhere - deployment is already here!
The ICT revolution is not over. Computers and data are continuing to transform firms and industries. Emergent social crises (alienation, misinformation, and polarization) and economic issues (rising inequality, monopoly power, and outsourcing) are unresolved. Bodrožić and Adler lay out four scenarios for the future of the ICT revolution. Will the ICT revolution proceed as Digital Oligarchy, Digital Democracy, Digital Localism, or Digital Authoritarianism? We will discuss and analyze these in a companion article.
But there is an important complication for those scenarios – an overlapping technological revolution driven by a new, broadly applicable technology (AI). Unlike Bodrožić and Adler (who wrote before the release of ChatGPT), we believe that AI is not just another application of the “computer and data” revolution, but the start of a new age. We address AI as well in our discussion of the scenarios.
Business Implications of the History for the AI Revolution
The AI revolution has just begun its installation phase, with a flood of investment coming. Unlike earlier revolutions, the leading innovators – particularly Microsoft and Google – are already behemoths with enormous resources deployed. But while other businesses are unlikely to dominate the core AI technology, the history of earlier technological revolutions suggest important opportunities:
Technology revolutions require complementary innovations and supporting infrastructure. For example, there are sure to be profitable opportunities in the Internet of Things.
During the installation phase, core technologies face challenges outside their initial application areas. AI applications are highly specialized (there is not yet a “general AI”). Developing and deploying custom applications may require expertise and insight that the tech giants do not have.
Most importantly, AI – like other new core technologies – is not an easy fit into existing business processes and organizational structures. Businesses that adjust successfully will have an enormous advantage, and this should be a corporate priority across a wide range of industries.
____
1Zlatko Bodrožić, Paul S. Adler (2022) Alternative Futures for the Digital Transformation: A Macro-Level Schumpeterian Perspective. Organization Science 33(1):105-125. https://doi.org/10.1287/orsc.2021.1558
2Schumpeter JA (1939) Business Cycles: A Theoretical, Historical, and Statistical Analysis of the Capitalist Process (McGraw-Hill, New York)
3Bodrožić and Adler, p. 109
Hey, it's interesting about that