How fast is generative AI adoption compared to earlier technologies?

Bick, Blandin and Deming report results from the Real-Time Population Survey (RPS), a nationally representative US labor-market survey of adults aged 18-64, fielded in August and November 2024 with more than 10,000 respondents. They find that "nearly 40 percent of the U.S. population age 18-64 uses generative AI," with "23 percent of employed respondents" having used it for work "at least once in the previous week" and 9 percent every work day. Benchmarked against the Current Population Survey's historical Computer and Internet Use supplement, they report that "work adoption of generative AI has been as fast as the personal computer (PC), and overall adoption has been faster than either PCs or the internet." Specifically, "In 1984, 25 percent of workers reported using computers for their job, compared with 27 percent of workers who report using genAI for their job in 2024" — comparing year three of the IBM PC's release to year two of ChatGPT's.

The authors attribute the faster-than-work pace of non-work adoption to cost and friction: "Computer adoption required the purchase of expensive hardware, and the internet required the purchase of a modem and an internet service provider contract, whereas ChatGPT is available for free or with a low-cost subscription, and using it does not require any technical expertise." They also find demographic adoption curves for genAI and PCs resemble each other — "greater early usage among younger, more educated workers in professional occupations" — with one divergence: "women were earlier users of PCs, in part because of rapid adoption of computers in white-collar clerical occupations," a pattern genAI adoption does not replicate in their data.

This adoption-speed framing sits alongside other recent measurements of where and how genAI use concentrates. Who adopts enterprise AI first and how do they use it? measures firm-level concentration from the supply side (one vendor's enterprise logs); Bick, Blandin and Deming instead measure population-level incidence through a general household survey, and find adoption "broadly distributed" across occupation groups (every group between 15 and 50 percent) rather than concentrated in a few firm types. Their finding that a third of respondents use genAI outside work, with growth outpacing work use, also complements How is ChatGPT actually being used by real people?, which measures the same work/non-work split directly in ChatGPT conversation logs rather than via self-report.

The RPS data establish adoption incidence and self-reported frequency, not productivity or earnings outcomes — those are addressed separately in What is generative AI's actual aggregate productivity gain today?. The comparison to PCs and the internet is also explicitly a speed-of-uptake analogy, not a claim that genAI's downstream economic effects will match computerization's; the authors note only that the resemblance in adoption curves is "notable" given that PC adoption preceded "rising aggregate productivity and growing income inequality," leaving open whether a similar trajectory will follow.