Borrowed expertise: Why AI’s productivity boom may not survive the generation that built it
Borrowed expertise: Why AI’s productivity boom may not survive the generation that built it
Publish Date: 2026-07-10 09:07:00
Source Domain: www.brookings.edu
The productivity numbers from generative artificial intelligence (AI) are remarkable, and they are real. Across knowledge industries, output per worker is rising in ways that would have been hard to imagine three years ago. The natural conclusion, drawn by many, is that we are at the early stage of a long economic boom, with the gains compounding as adoption deepens.
But this conclusion rests on a hidden assumption, and that assumption is becoming less true every day. The productivity miracle we are observing is produced, in large part, by people whose expertise was built before AI existed. They are extraordinarily good at directing these tools because they have spent careers training the kind of judgment that knows what to ask, what a good answer looks like, and where a confident-sounding model is likely to be wrong. They are extracting value from AI in part because they paid the developmental cost that AI now lets others avoid.
The conditions that produced this expert class are eroding. The pipeline that would replace them is being attenuated. And the productivity story we tell ourselves about the next 20 years assumes the steady arrival of new senior experts who will, in fact, not arrive on schedule.
The familiar AI and inequality concerns are about access and displacement: who can use the tools and whose jobs are automated. The argument here is different. It is about cognitive development, the conditions under which expertise gets built, and what happens when those conditions are quietly removed for an entire generation. The corollary is what such a society does about innovation, paradigm change, and the creation of new knowledge, which I will explore in a second piece.
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