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AI adoption at work is broad but shallow

Economists have taken another stab at assessing the impact of generative AI adoption on different occupations and have found that adoption is broad but not very deep. While generative AI reaches 80 percent of occupations and more than 40 percent of tasks, in most of these occupations fewer than half of workers adopt it. Occupational […]

By deepak · September 1, 2026 · 3 min read

Economists have taken another stab at assessing the impact of generative AI adoption on different occupations and have found that adoption is broad but not very deep. While generative AI reaches 80 percent of occupations and more than 40 percent of tasks, in most of these occupations fewer than half of workers adopt it. Occupational use is high in professions where you’d expect – in management and professional occupations, particularly those that are related to finance, business, and computers. It’s lowest in personal service occupations and jobs requiring manual activity or interpersonal interaction. That in and of itself isn’t surprising – other studies have suggested as much. But AI companies that have looked at occupational exposure to generative AI (Anthropic, Microsoft, OpenAI) based on chat logs come up with results that differ from those described in “What Work Does Generative AI Do?” The paper [PDF], by authors Alexander Bick (Federal Reserve Bank of St. Louis), Adam Blandin (Vanderbilt), David J. Deming (Harvard), and Tyler R. Schumacher (Vanderbilt), measures how workers actually use generative AI for their jobs by analyzing Real-Time Population Survey (RPS) data. The measurement discrepancy is the result, the authors say, of chat log classifiers that associate chats with a few tasks that have generic, activity-based descriptions like “Edit written material or documents.” The problem with this approach is that when OpenAI data concludes 15 percent of chats involve that sort of editing, those figures don’t match up with the US Department of Labor’s O*NET database, where only 2.4 percent of workers are in jobs that include that task. The result, the researchers say, is that the exposure figures from vendors likely overstate how much generative AI is actually relevant to people’s jobs. “GenAI is used in many occupations and tasks, but few of these exhibit very high adoption rates,” the authors state. “For example, four out of five detailed occupations have adoption rates above 20 percent, but only one out of six occupations exceed 70 percent adoption.” Most occupations exhibit relatively low adoption rates, but for a few, the figure is substantial. About 15 percent of occupations had adoption rates above 70 percent (largely computer-oriented). And in terms of tasks, only 2.8 percent of tasks had adoption rates above 50 percent and none surpassed 70 percent. Overall, as of May 2026, 55 percent of US adults between the ages of 18 and 64 used generative AI for non-work reasons and 45 percent of US adults used GenAI for work, according to the paper. The overall adoption rate (work or otherwise) is 62 percent. One thing that drives AI adoption, they say, is experience. Those who start using it in one domain tend to adopt it in other domains. Thus the researchers argue it’s at least as important to understand why some workers adopt AI and some don’t as it is to understand which tasks it can handle. ®

Source: Read the original article on www.theregister.com

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