Estimating AI productivity gains
Anthropic (AI lab research) · 25 Nov 2025
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Where this sits in the debate
- Will AI actually boost productivity and growth? · its finding supports the claim (why studies differ)
Direction of the finding as read from the abstract by an AI model (AI-written).
Source excerpt
Extrapolating these estimates out suggests current-generation AI models could increase US labor productivity growth by 1.8% annually over the next decade — roughly twice the run rate in recent years. But this isn’t a prediction of the future, since we don’t take into account the rate of adoption or the larger productivity effects that would come from much more capable AI systems. Our analysis has limits. Most notably, we can’t account for additional time humans spend on tasks outside of their conversations with Claude, including validating the quality or accuracy of Claude's work. But as AI models get better at time estimation, we think our methods in this research note could become increasingly useful for understanding how AI is shaping real work. This gives us a new lens for understanding how AI’s economic impacts over time, which we will track going forward as part of our Economic Index : Computing these estimates based on real-world Claude conversations gives us a new lens to understand AI productivity. This complements other approaches, like lab studies in narrow domains, or government statistics which provide more coarse-grained insights. We will track how these estimates change over time to get an evolving picture of these issues as capabilities and adoption continue to progress. As part of the Anthropic Economic Index , we have documented how people use Claude across different tasks, industries, and places. We’ve captured the breadth of uses—how people use Claude for legal, scientific, and programming tasks—but not their depth . How substantial are the tasks for which people use Claude, and how much time does Claude save them? The current version of the Economic Index can't capture this within-task heterogeneity —for instance, it can’t distinguish report-writing tasks that take five minutes from those that take five days, or financial modeling tasks that take an afternoon from those that take a few weeks. This makes it difficult to assess AI's economic effec
About this publication
Lab or institute research, not peer reviewed. A report or blog post published by an AI lab or research institute on its own site. It has not been through independent peer review, and the publisher may have a stake in the findings.
- Published
- 2025 (11 months ago)
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□ added to this collection in 2026.
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