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![Measuring the Impact of AI on Productivity: Cross-Sectoral Evidence from the U.S. and Eighteen Other Economies Post-ChatGPT
76 Pages Posted: 28 Apr 2026 Last revised: 5 Jun 2026
Benjamin Verschuere
Liminal Capital
Angus Cameron
Liminal Capital
Date Written: April 27, 2026
Abstract
We provide the first cross-country sectoral measurement of artificial intelligence’s contri- bution to trend productivity growth globally, identified from observed sectoral outcomes through 2025Q4 rather than from forecasts of diffusion. Using a panel difference-in- differences specification with AI exposure measured by the Workflow Completeness construct (C∗) of Verschuere and Cameron (2026a), we estimate that AI is contribut- ing approximately $1.26 trillion per year across the United States, the EU 12, and China combined at the end-of-2025 run-rate. The U.S. accounts for $878 billion (95 percent CI [$602B, $1,155B]) across five primary sectors covering roughly 54 percent of GDP, raising aggregate growth on this base to +5.0 percent per year against a +2.2 percent counterfactual. The EU 12 pooled panel contributes $138 billion (95 percent CI [$23B, $254B]) and China $240 billion (95 percent CI [$116B, $365B]). The result holds under the primary inference cascade (wild cluster bootstrap and permutation), falls short of significance only under its single most conservative bootstrap variant, and survives ten alternative-mechanism tests (eight conducted in this paper, two adopted from the companion papers).](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:weypikbrwodr2fsanloqjx6s/bafkreialaytlx6mkism7olyramk2ccxp7mdwd4alcbamcijbd6wcnwl3eq)
