AI is different from other technological breakthroughs in the extent that it can radically transform society and even what it means to be human, but its adoption among users has been very different from other technologies too.
Venture capitalist Marc Andreessen recently highlighted a fascinating reversal in how transformative technology spreads through society. Speaking about artificial intelligence adoption patterns, the Netscape co-founder and Andreessen Horowitz partner described how AI represents a complete inversion of the institutional-first model that characterized previous technological revolutions, particularly the computer age.
Andreessen traced the historical pattern that dominated the 20th century: “The old model of adapting—actually computers when computers came out—the old model was the largest institutions get technology first and then everybody else gets it later. And so the way the computer rolled out was the government actually got mainframe computers first starting in the 1940s. And then big companies got computers, mainframes in the 1950s, 1960s. Small companies started to get computers—mini, we were called mini computers at the time—in the 1970s. And then we as individuals only got PCs in the 1980s.”
The implications of this cascade were profound: “So it took 40 years for basically technology to cascade down from the largest organizations in the world to small businesses and to the individual.”
But with AI, Andreessen observed a striking departure from this pattern: “This technology, AI, is going the opposite. What we’re finding is consumers are adapting the fastest—just individuals in their lives. The small businesses are then adopting right after that. Their companies are then following small companies. And so, the companies on that list, some of them are doing interesting things. But in general, big companies right now are pretty tied up in knots internally, kind of in all their processes and in all their legacy systems and all their organization and training and their unions and all the other issues they have to deal with. They’re actually relatively slow to adopt compared to individuals and small businesses.”
At the bottom of this inverted pyramid sits government: “And then government is the late adopter, right? And so governments, of course, are already trying to figure out how to adapt this technology, but they’re not adopting it very fast because they can’t, because of all their rules and systems and bureaucracy. And so there’s been a real inversion of how technology moves through our society. That’s really become—AI’s becoming a case study for.”
This reversal carries significant implications for how AI will reshape economic and social structures. The consumer-first adoption pattern explains why ChatGPT reached 100 million users in just two months, becoming the fastest-growing consumer application in history. Meanwhile, enterprises have been slower to implement AI at scale, grappling with data governance concerns, integration challenges with legacy systems, and regulatory uncertainty. Recent surveys indicate that while over 80 percent of knowledge workers have experimented with generative AI tools, only a fraction of large enterprises have moved beyond pilot programs to full deployment. Government adoption lags even further behind, with public sector organizations constrained by procurement processes, security requirements, and risk-averse cultures. This bottom-up diffusion pattern suggests that the competitive advantages of AI may accrue first to nimble startups and individual entrepreneurs rather than to incumbents, potentially accelerating creative destruction across industries and challenging the dominance of established institutions in ways that previous technological waves did not.