Economic Index: New building blocks for AI use

Anthropic (AI lab research) · 15 Jan 2026

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Where this sits in the debate

Will AI destroy more jobs than it creates?

Direction of the finding as read from the abstract by an AI model (AI-written).

Source excerpt

At Anthropic, we’re measuring real-world AI use on an ongoing basis to answer questions exactly like these. Our privacy-preserving analysis method allows us to learn more about conversations on Claude.ai (capturing uses by consumers) and our first-party API (mostly capturing uses by businesses). 1 In past reports, we’ve assessed AI tasks by occupation and wage level , looked more closely at software development , and studied AI use by country and by US state . We’re now adding a new level of detail to our Economic Index. In our fourth report, we’re introducing what we’ve called economic primitives : a set of five simple, foundational measurements to track the economic impacts of Claude over time. Our initial set includes task complexity, skill level, purpose (work, education, or personal use), AI autonomy, and success. 2 We derive these primitives from asking Claude to answer a common set of questions about every conversation in our sample for this report. These primitives provide a leading indicator of AI’s potential economic impacts—and allow us to answer far more complex questions about how AI is already changing jobs. Our latest report, which samples conversations from November 2025 (predominantly using Claude Sonnet 4.5), uses our primitives to explore a wide range of questions that we wouldn’t otherwise be able to answer—including how Claude’s task-level success rates change for more complex tasks, and whether the use of Claude to date might portend a net-deskilling effect on many jobs. You can read the fourth Economic Index report here . Below, we summarize its results. We applied our economic primitives to questions about individual tasks, occupations, and then the possible aggregate impacts of the changes we observe. (Our full methodology—including details on how we tested the accuracy of our primitives—is described in chapter two of the full report .) We found that more complex tasks were sped up the most by Claude. We measure this by what Claude estimates

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Lab or institute research, not peer reviewed.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 (9 months ago)
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Economic Index: New building blocks for AI use

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