In January 2026, Microsoft released data that should have reframed every conversation about AI competition. The company had been tracking what it calls "AI diffusion"—the percentage of working-age populations actually using generative AI tools—across nations worldwide. The results were striking, but not in the way the American tech industry expected.
The United States, which leads the world in AI infrastructure, frontier model development, and venture capital investment, ranked 24th in AI usage among its working-age population. Twenty-fourth. Behind Ireland, behind Spain, behind Belgium. The usage rate: 28.3 percent.
The United Arab Emirates ranked first, at 64 percent adoption. Singapore second, at 60.9 percent. These are not countries known for frontier AI research. They have no models competing with GPT-5 or Claude. They didn't pioneer transformer architectures or invent reinforcement learning from human feedback. They did something different: they diffused capability throughout their populations while America was busy inventing it.
I've been thinking about this data for weeks now, because it crystallizes something I've suspected for a long time about how technological advantage actually works. The conventional wisdom—that the nations and organizations leading AI research will dominate the AI era—is almost certainly wrong. And the historical evidence for why it's wrong is overwhelming, if you know where to look.
The Diffusion Thesis
In 2022, Jeffrey Ding, a political scientist at George Washington University, published research that should have upended how we think about technology competition. His book, Technology and the Rise of Great Powers, won the 2025 Lepgold Book Prize, but its central finding remains underappreciated: across three industrial revolutions, what determined economic advantage wasn't who invented breakthrough technologies. It was who diffused them.
"Where innovations are adopted more effectively is more important than where they are first introduced," Ding argues. The insight seems counterintuitive until you examine the evidence.
Consider the Second Industrial Revolution. Germany dominated the frontier technologies of the era—chemicals and electrical equipment. By 1900, Germany produced 90 percent of global synthetic dyes and controlled roughly 50 percent of world electrical equipment exports. These were the AI equivalents of their time: transformative, general-purpose technologies that would reshape every industry they touched.
Yet the United States became the preeminent economic power. Not Germany. How?
The answer lies in diffusion infrastructure. In 1862, the Morrill Act financed land-grant colleges dedicated to mechanical arts. Engineering schools multiplied from 6 in 1862 to 126 by 1917. By 1900, 88 percent of mechanical engineering students were in land-grant colleges emphasizing practical, applied training—not elite research. The result: U.S. machine intensity was more than twice that of Britain and Germany by 1907.
American advantage came not from breakthrough inventions but from what British observers called "adaptation of special apparatus to a single operation in almost all branches of industry." Americans didn't invent interchangeable manufacturing. They diffused it—across sewing machines, bicycles, typewriters, and eventually automobiles. The resistance to diffusion wasn't technical; it was cultural. British manufacturers saw American methods as crude, unsophisticated, lacking the craft wisdom that "real" engineering required.
The pattern repeats with eerie consistency. Britain's First Industrial Revolution succeeded not because of heroic inventors like James Watt, but because of what economic historians call "tweakers" and "implementers"—ordinary engineers who spread mechanization throughout the economy. Britain's advantage wasn't elite scientific genius. It was "the average level of technical literacy" among machinists. Widening the base of capability, not deepening the peak.