Anthropic Research released the Anthropic Economic Index, analyzing millions of Claude.ai conversations. The index reveals that AI usage is heavily concentrated in software development and technical writing. It also shows how AI impacts tasks across various occupations and whether it serves to augment or automate work.
In the coming years, AI systems will have a major impact on the ways people work. For that reason, we're launching the Anthropic Economic Index , an initiative aimed at understanding AI's effects on labor markets and the economy over time.
The Index’s initial report provides first-of-its-kind data and analysis based on millions of anonymized conversations on Claude.ai , revealing the clearest picture yet of how AI is being incorporated into real-world tasks across the modern economy.
We're also open sourcing the dataset used for this analysis, so researchers can build on and extend our findings. Developing policy responses to address the coming transformation in the labor market and its effects on employment and productivity will take a range of perspectives. To that end, we are also inviting economists, policy experts, and other researchers to provide input on the Index.
The second largest category was “arts, design, sports, entertainment, and media” (10.3% of queries), which mainly reflected people using Claude for various kinds of writing and editing. Unsurprisingly, occupations involving a high degree of physical labor, such as those in the “farming, fishing, and forestry” category (0.1% of queries), were least represented.
Our new paper builds on a long line of research on the labor market impact of technologies, from the Spinning Jenny of the Industrial Revolution to the car-manufacturing robots of the present day. We focus on the ongoing impact of AI. We don’t survey people on their AI use, or attempt to forecast the future; instead, we have direct data on how AI is actually being used.
Our research began with an important insight from the economics literature : sometimes it makes sense to focus on occupational tasks rather than occupations themselves . Jobs often share certain tasks and skills in common: for example, visual pattern recognition is a task performed by designers, photographers, security screeners, and radiologists.
Certain tasks lend themselves better to being automated or augmented by a new technology than others. We’d therefore expect AI to be adopted selectively for different tasks across different occupations, and that analyzing tasks—in addition to jobs as a whole—would give us a fuller picture of how AI is being integrated into the economy.
This data provides empirical insight into how artificial intelligence is practically applied across industries, showing a stronger trend toward human augmentation than outright automation.