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Anthropic Economic Index report: Learning curves

Anthropic (AI lab research) · 24 Mar 2026

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Source excerpt

This latest report studies Claude usage in February 2026, building on the economic primitives framework introduced in our previous report (which used data from November 2025). Our sample covers February 5 to February 12, three months following the release of Claude Opus 4.5 and coincident with the release of Claude Opus 4.6. We first document how usage has changed relative to our previous reports: the rate of augmentation, collaborative interaction where the AI complements the user’s abilities, increased slightly in both Claude.ai and API traffic. In Claude.ai, usage diversified, with the top 10 tasks accounting for a smaller share of usage last month than in November 2025. As a result of this diversification, the average conversation in Claude.ai had a slightly lower-wage task than in previous reports. We then focus on an important determinant of Claude’s impact on the labor market and the broader economy: learning curves in Claude adoption. We present evidence that high-tenure users have developed habits and strategies that allow them to better harness Claude’s capabilities. Indeed, we document that more experienced users not only attempt higher-value tasks, but are also more likely to elicit successful responses in their conversations. In the first chapter, we revisit findings from our previous Economic Index report , published in January 2026. We find that: A central finding in the Economic Index is that early adoption of Claude is very uneven: Claude is used more intensely in high-income countries, within the US in places with more knowledge workers, and for a relatively small set of specialized tasks and occupations. An important question is how inequality of adoption might determine where and to whom the benefits of AI will accrue. If, for example, effective AI use requires complementary skills and expertise—which we argued in our previous report —and if such skills can be acquired through use and experimentation, then the benefits from early adoption may be

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Lab or institute research, not peer reviewed.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
2026 (7 months ago)
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