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AI productivity: not a miracle yet
29/05/2026
U.S. productivity is improving. In aggregate economic data, however, the AI dividend remains easier to imagine than to measure.
Early in Douglas Adams’ “The Hitchhiker’s Guide to the Galaxy,” Arthur Dent decides that “Don’t Panic” is the first helpful or intelligible thing anybody has told him all day. Not bad advice for anyone searching U.S. productivity data for employment or investment clues on the impact of AI either.
Our Chart of the Week compares year-on-year growth in U.S. nonfarm output per hour with year-on-year growth in real compensation per hour since 1985. Productivity has recovered from the 2022 post-pandemic slump and is now growing faster than real pay. So far, so good: the economy is producing more per hour worked, while households’ purchasing power is also rising, albeit more slowly.
That fits the pattern AI optimists would like to see. Incoming U.S. Federal Reserve (Fed) Chair Kevin Warsh, for example, has long argued that AI-driven productivity gains could be structurally disinflationary, by lowering production costs and helping to restrain output prices. Real wages would rise without nominal wage pressures getting out of hand, eventually making lower interest rates easier to justify.
The trouble is that central bankers can rarely bet on a single causal mechanism, even when they have correctly identified one. “Outside the economic textbooks, all things are rarely equal,” notes Christian Scherrmann, Chief U.S. Economist at DWS. Warsh may first have to deal with oil prices and inflation expectations. In the short run, the AI investment boom may even make that harder, by lifting demand for scarce inputs, from capital and copper to electricians.
Based on the evidence so far, task-level productivity gains appear to be real, but concentrated, and not necessarily where demand is hottest. Moreover, many hard-to-automate tasks still require judgment, context and organizational change, as well as manual dexterity. As in earlier technological shifts, AI will probably move relative prices and wages long before its economy-wide impact becomes clear.[1]
Price signals tell households and companies when and how to adjust – perhaps even nudging some software programmers to retrain as electricians. Such temporary skill mismatches may help explain why new technologies take time to show up in productivity statistics. For now, Arthur Dent’s lesson still applies: don’t panic – and don’t mistake the first intelligible signal for the final answer.
Productivity gains are visible — but not yet miraculous
Sources: Bureau of Labor Statistics, Haver Analytics, DWS Investment GmbH; latest available data as of Q1 2026.
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