The Trump White House is pitching artificial intelligence as the next American economic miracle, one that delivers greater prosperity and secures US military dominance. But technological revolutions tend to unfold on their own timetable, not on a political one.
History offers plenty of humbling precedents. Electrification, computers, and the internet all transformed daily life—yet US per-capita GDP growth has stubbornly hovered around roughly two percent per year for the past 150 years. These general-purpose technologies reshaped the economy and our lives without visibly bending its long-run growth trend. AI may prove more powerful than any of them, but it will not automatically rewrite macroeconomic laws.
Economist Charles I. Jones of Stanford considers two basic paths forward. Yes, AI could spark a historic growth acceleration, as many Silicon Valley folks—what I term the “San Francisco Consensus”—predict. It also might look like “business as usual,” according to what Jones and many economists on Wall Street and in Washington forecast, the “Acela Corridor Consensus.”
Both futures are totally plausible, as Jones sees things. Economic models in which AI steadily automates more tasks can generate much faster growth, even approaching a self-reinforcing innovation flywheel. In the most optimistic case, AI becomes a “country of geniuses in a data center,” turbocharging R&D, scientific discovery, robotics, and energy innovation. In this scenario, the US achieves escape velocity from that two percent trend—what Jones calls the “Moore’s Law of Macroeconomics”—for an upside breakout.
Yet Jones also highlights a structural brake that policymakers need to consider: Economic progress is constrained by weak links. Production depends on many complementary tasks, and automating some of them—even lots of them—doesn’t necessarily super-accelerate the whole system. Output remains limited by the hardest, slowest-to-automate bottlenecks.
Consider this: Even if AI made all “thinking work”—planning, designing, managing, analyzing—essentially free, the economy would still be limited by physical production, energy, materials, logistics, infrastructure, and other real-world constraints. That’s why automating all cognitive labor might boost output by roughly 50 percent, not infinity—a massive gain, but still bounded by the parts of the economy that can’t scale instantly. From the paper:
For example, knowledge work in the U.S. economy might get paid something like 1/3 of GDP. What if we automated all cognitive labor with infinite output on the tasks that it performs? This would raise GDP by 50 percent. On the one hand, if this occurred over the course of a decade, it would raise growth rates by something like 5 percent per year, which would be huge. But still, that would be a one-time gain and it is perhaps surprising that having access to infinite output of the tasks currently performed by cognitive labor might only raise GDP by 50 percent.
This is why, in Jones’s telling, AI becomes genuinely transformative in the way the superoptimists hope only if it moves beyond software and starts breaking the economy’s real-world bottlenecks. Truly rapid growth becomes more plausible if AI is paired with advanced robotics to automate the physical side of the economy. Smart machines for bits and atoms.
The White House is promising an AI-driven renaissance now, but Jones’s reading of economic history suggests the biggest gains may arrive more slowly—diffusing across firms, reshaping workflows, and requiring waves of complementary investment before they show up in headline productivity statistics. As with earlier general-purpose technologies, Americans may “see AI everywhere but not in the GDP data” for years, even as the underlying transformation quietly builds amid public complaints about data centers and perceived job impacts.
This is not a counsel of pessimism. Jones is notably bullish on AI’s long-run potential, calling it “likely the most important technology we have ever developed.” Over time, he expects its impact to surpass that of the internet by a wide margin, reshaping living standards and expanding what societies can invent and build. The real issue, then, is whether institutions and politics can absorb the disruptions that come with a technology powerful enough to change the economy’s trajectory since the 19th century.
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