Throughout history, General Purpose Technologies have reshaped economies, industries, and societies. Steam power, electricity, and computing all followed a familiar trajectory – initial invention, slow diffusion, and eventual transformation that restructured industries and economies. Each of these transitions took decades, often constrained by infrastructure needs, workforce adaptation, and institutional resistance. Yet today, as we stand at the intersection of artificial intelligence, synthetic biology, and quantum computing, the question arises: Will this General Purpose Technology cycle break historical patterns and accelerate system-level change faster than ever before?

This is not just a theoretical question. It has profound implications for economies, businesses, and geopolitics. If this transformation happens in 15 years instead of 50, societies must prepare for a radically different future much sooner than expected. If the cycle slows down due to regulatory, economic, or societal resistance, the transition will stretch over decades, following historical precedent. And if diffusion occurs asymmetrically – where authoritarian regimes accelerate while democratic systems regulate and resist – global power dynamics could shift in unpredictable ways.

This is an exercise in rehearsing the future – exploring the scenarios that could shape how quickly this cycle unfolds.

SCENARIO 1: A COMPRESSED TIMELINE – WHY THIS GPT CYCLE WILL BE FASTER

There are several reasons to believe that this wave of technological change will unfold more rapidly than previous General Purpose Technology transitions. Unlike past cycles, which were largely driven by a single foundational technology, today’s AI, synthetic biology, and quantum computing breakthroughs are converging, reinforcing each other’s progress. This interdependence creates positive feedback loops, accelerating both research and application. AI is already enabling quantum advancements, which in turn will accelerate materials science and biological innovation. The convergence of these technologies shortens the timeline from invention to application, allowing industries to leapfrog traditional development cycles.

Geopolitics is another key accelerant. Unlike the industrial revolutions of the past, which were largely centered around a single dominant power, this General Purpose Technology cycle is unfolding in a world of multipolar technological competition. China’s ambition to achieve global dominance in AI, synthetic biology, and quantum computing is pushing the U.S. and Europe to respond with urgency. This race is not just about economic opportunity – it is about strategic necessity. As China rapidly integrates AI into governance, manufacturing, and military applications, Western nations will be forced to accelerate their own diffusion strategies to avoid losing ground.

The digital infrastructure already exists to support rapid adoption. Unlike electricity, which required the construction of power grids, or computing, which relied on decades of hardware evolution, AI, quantum computing, and synthetic biology are building on mature cloud computing, global data networks, and digital platforms that are already in place. This eliminates one of the biggest historical barriers to diffusion. AI applications can be deployed over the internet, quantum breakthroughs can integrate into existing cloud architectures, and synthetic biology benefits from AI-driven protein modeling.

If these acceleration forces hold, the transition to system-level change could happen in 15 years rather than 50. The defining challenge will be whether societies, institutions, and businesses can adapt as quickly as the technology itself.

SCENARIO 2: THE HEADWINDS THAT COULD SLOW DIFFUSION

Despite these acceleration forces, history suggests that disruptive technologies rarely diffuse as quickly as early adopters predict. The shift from steam power to industrial manufacturing took more than a century. Electricity took decades to scale because factories needed to redesign their workflows before they could realize its full benefits. Computing required not just hardware advances but also organizational adaptation and new business models before it truly transformed the economy.

A similar dynamic could slow the current General Purpose Technology cycle. Regulation remains a major bottleneck, particularly in democratic societies where AI and biotech raise ethical concerns. Data privacy laws, ethical AI guidelines, and biotech regulations could create a fragmented adoption landscape, where innovation moves forward unevenly across industries and geographies. While businesses may want to integrate AI and synthetic biology rapidly, compliance requirements could drag out the transition over decades.

Workforce adaptation is another key constraint. While AI is progressing at an unprecedented pace, humans and institutions do not evolve as quickly as algorithms. Many industries still operate on legacy systems, and while AI and quantum computing promise revolutionary efficiency, implementing them at scale requires retraining workforces, updating business processes, and overcoming deep cultural resistance to change.

Geopolitical fragmentation could also slow diffusion. While China is aggressively pushing AI deployment through state-driven initiatives, the U.S. and Europe are engaged in a strategic technology decoupling to prevent dependency on Chinese AI and quantum computing. This could create a world where General Purpose Technology diffusion is slower due to national security concerns and supply chain constraints, rather than moving at full speed across a globalized economy.

If these friction points dominate, the timeline for system-level change could extend beyond 20 years, following historical patterns rather than breaking them.

SCENARIO 3: A DIVIDED WORLD – DEMOCRACIES LAG WHILE AUTHORITARIAN REGIMES ACCELERATE

A third scenario, and perhaps the most concerning, is one where General Purpose Technology diffusion happens asymmetrically. In this future, authoritarian regimes like China rapidly diffuse AI, synthetic biology, and quantum computing, while democratic nations slow down due to regulatory, ethical, and institutional barriers. This divergence would create two parallel technological ecosystems, with China and its allies racing ahead while the West debates the risks and controls necessary to govern these powerful technologies.

China already has a centralized approach to AI diffusion, integrating it into governance, military applications, and economic infrastructure without the bureaucratic delays seen in democracies. By exporting AI-powered surveillance, quantum-secure communications, and biotech advancements to its allies, China could create a fast-moving technological bloc that advances at a pace Western nations struggle to match.

Meanwhile, the U.S. and Europe could find themselves hamstrung by political fragmentation. AI safety debates, corporate resistance to radical transformation, and slow-moving government policies could create a widening gap between technological breakthroughs and their real-world application. In this scenario, General Purpose Technologies continue to advance rapidly in research and development, but their adoption and integration into industries, governance, and infrastructure lag behind. If democratic nations fail to act decisively, they risk losing their technological edge – not because they lack innovation, but because they struggle to deploy and diffuse their innovations at the speed necessary to remain competitive.

This scenario suggests a future where the global balance of power is reshaped not by military conquest, but by the speed of technological adoption. Nations that diffuse General Purpose Technologies rapidly will define the rules of the future economy, while those that hesitate will find themselves adapting to systems they did not create.

CONCLUSION: WHICH FUTURE WILL PLAY OUT?

The trajectory of this General Purpose Technology cycle is uncertain. It may accelerate at an unprecedented pace, compressing decades of change into a single generation. It may follow the historical pattern of slow diffusion, constrained by regulation, institutional inertia, and workforce adaptation. Or it may create a world divided, where authoritarian states race ahead while democracies struggle with the complexities of ethical governance and national security concerns.

What is certain is that this General Purpose Technology cycle will not follow a single trajectory – it will unfold differently across nations, industries, and societies. Businesses and governments must prepare for all scenarios, recognizing that the speed of diffusion, not just the pace of invention, will determine who leads in the next era of technological dominance.

Just as COVID-19 acted as a forcing function that accelerated trends like remote work, telemedicine, and remote learning, geopolitical competition is now forcing the rapid diffusion of AI, synthetic biology, and quantum computing. National security concerns, economic decoupling, and global power shifts are eliminating inertia and compelling nations to deploy these technologies at scale. The question is not just which country will invent the most powerful AI models or quantum breakthroughs, but which will diffuse and integrate them into infrastructure, industry, and governance fast enough to maintain a strategic edge.

Rehearsing these futures is not about predicting a single outcome – it is about preparing for all possibilities and making the strategic decisions that will shape the future. The race is not just to innovate, but to adapt, deploy, and govern these technologies at the speed the world demands.