Tracking AI’s Real-Time Footprint On The Labor Market
Stanford HAI (AI lab research) · 21 Oct 2026
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Where this sits in the debate
- Will AI actually boost productivity and growth?
- Will AI destroy more jobs than it creates? · its finding supports the claim (why studies differ)
Direction of the finding as read from the abstract by an AI model (AI-written).
Key takeaway AI-written
Stanford HAI's Digital Economy Lab describes monthly AI Economic Indicators dashboards that track employment, wages, aggregate outcomes, hiring and AI usage. Early readings show employment in AI-exposed jobs such as software development and customer service down more than 4% this year.
Source excerpt
Employment in AI-exposed jobs like software development and customer service has dropped by more than 4% this year, while occupations that are reliant on AI automation are showing slowing or shrinking job growth. Those are some of the key findings from a new set of “dashboards” launched in June 2026 by Stanford HAI’s Digital Economy Lab (DEL). Updated monthly, these dashboards – called AI Economic Indicators – track AI’s economic footprint in real time. Unlike official statistics that report on longer-term trends, these new tools capture swift shifts as they happen. “At DEL, we’re really interested in understanding the economic impact of AI not only because it has amazing potential, but also because it’s been adopted perhaps more rapidly than any other technology ever,” says Connacher Murphy , who spearheaded the Indicators project. “The issue we’ve kept running into is that it’s very hard to get a big, aggregate view of what’s actually happening, what’s just hype, and what is genuine economic change. Our Indicators can help us get a clearer picture.” The project pulls data from private companies, academic researchers, and government statistical agencies and organizes it into three primary dashboards that track trends in employment and wages, aggregate outcomes, consumer surplus (the difference between what someone is willing to pay and the actual price they pay), hiring and skills, and AI usage. One dashboard, the Transformation Tracker, monitors 12 macroeconomic indicators to gauge if any significant changes can be attributed to AI. “We’re asking, ‘Do we see anything happening in aggregate with these bigger, moving statistics?’” Murphy explains. True to its name, the Canaries Dashboard is designed as an early-warning indicator to detect emerging workforce trends. It tracks employment across occupations , with workers grouped according to high and low AI exposure. The dashboard was built in collaboration with ADP Research, a New Jersey-based, data-driven institute
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