Most great technological shifts begin as curiosities before they remake the world. A press that copied books sparked an information revolution. A pump that drained mines powered the steam age. A lamp that lit a room heralded electricity. None looked like revolution at the time—only later did they reorder economies and empires.
Artificial intelligence has arrived in the opposite way: loud, hyped, seemingly everywhere at once. Yet the spectacle obscures a deeper reality: the true disruption is still ahead. Economists call technologies like the steam engine or electricity general-purpose technologies — tools that unlock new industries and ripple across economies. AI fits that description, but it is also something more: a meta-technology that rewires how every other tool is used. GPTs follow a familiar arc — initial frenzy, then the grind of infrastructure, upheaval, and redesign. AI will follow the same path.
Where the Shock Hits First
Finance is an information industry, with participants in constant search of data and insights on everything from risk and credit to pricing and other factors — and that makes it ground zero for AI.
For years, algorithms worked quietly in the back office, flagging fraud or parsing transcripts. Now the front office is being transformed. Hedge funds already analyze satellite images of oil tankers to anticipate supply shifts before official data. Banks are embedding AI in credit scoring, fraud detection, and compliance. Asset managers train proprietary models to spot correlations too fast for humans, while robo-advisors evolve into personalized engines adjusting portfolios for tax situations, ESG goals, and life events. The promise is faster insights and adaptive portfolios. The risk is convergence: too many firms using similar models can trigger cascades, as in the “quant quake” of 2007. Regulators are scrambling to demand transparency, audit trails, and stress testing.
Health care is also being reshaped. AI scribes are halving doctors’ documentation time, freeing them to focus on patients. In drug discovery, firms like Insilico have advanced AI-designed molecules into human trials, compressing a decade-long process into just a few years.
Retail is shifting from shelf space to data. Walmart uses predictive AI to forecast demand spikes and reroute supply chains, while e-commerce platforms adjust millions of product prices in real time. Generative tools are even designing clothing lines based on live consumer trends.
And in education, Khan Academy’s “Khanmigo” shows how AI tutoring, once the preserve of elites, can now scale to millions — while raising sharp questions about the value of credentials in a world where knowledge is everywhere.
Other sectors — manufacturing, media, transportation — are hardly immune. Finance, health care, retail, and education simply illustrate the range: AI that touches our money, our bodies, our consumption, and our minds.
Every great technology also rests on hidden scaffolding. For AI, that scaffolding is physical as much as digital: power, chips, fiber, and cooling. Data centers are the factories of the 21st century, running nonstop and consuming vast amounts of electricity. Grid reliability and energy density are suddenly strategic concerns. Renewables will play a role in decarbonization, but their intermittency is poorly matched to always-on workloads. Nuclear — especially small modular reactors — offers the most scalable, dense, zero-carbon source to match AI’s appetite.
Capital will flow accordingly. The biggest opportunities may not be in shiny applications but in the enablers: biotech platforms behind generative chemistry, data firms with irreplaceable information moats, logistics networks rewired by predictive AI. These are the picks and shovels of the machine intelligence age. Early gains accrue to firms with scale and foresight. For investors, the challenge is timing — ride the monopolists early, then pivot as benefits diffuse.
The New Chessboard of Power
This is not just another tech cycle. It is a reallocation of capital, labor, political power, and geopolitical advantage. In the early stages, concentration precedes diffusion: monopolists capture the lion’s share of value before benefits spread. And while disruption feels digital, the return of the physical is unmistakable. Innovation now depends on uranium mines, fabrication plants, transmission lines, and land. Software may eat the world, but it cannot run without power and concrete.
Above all, politics is becoming geopolitics. Control over energy, chips, and data is no longer just industrial policy — it is the foundation of national power. Nations that secure the scaffolding of AI will set the rules of the century.
History counsels humility: transformations take longer, and unfold stranger, than expected. Some firms will flame out, and some sectors will resist change longer than investors assume. But AI is the next great general-purpose technology — and a meta-technology that reorganizes how every other technology is deployed. The question isn’t whether it will transform societies. It’s who will own the scaffolding of the new industrial order—and with it, the levers of global power.
Edward Campbell is the founder & general partner of Red Hook Phoenix Investment Partners and an external advisor to Rosenberg Research Associates.
