AI job exposure highest among older, highly paid and educated workers, Anthropic report finds

Workers in professions most exposed to artificial intelligence are more likely to be older, female, highly educated and better paid, according to a new report from Anthropic.

The report, titled “Labour market impacts of AI: A new measure and early evidence,” introduces what the authors call a new metric of “observed exposure” to gauge how AI systems such as large language models are affecting different occupations.

“Workers in the most exposed professions are more likely to be older, female, more educated, and higher-paid,” the report said.

The findings challenge a common narrative that automation primarily threatens lower-skilled or lower-income jobs, suggesting instead that generative AI tools may disproportionately affect white-collar roles.

The study comes as companies across industries experiment with AI tools to automate tasks ranging from writing and coding to customer support and data analysis, raising questions about how generative AI will reshape white-collar employment in the coming years.

Anthropic researchers said their analysis combines theoretical capabilities of large language models with real-world usage data to assess how much work AI could potentially automate. The approach gives greater weight to tasks where AI replaces human work rather than simply assisting it.

“We introduce a new measure of AI displacement risk, observed exposure, that combines theoretical LLM capability and real-world usage data, weighting automated (rather than augmentative) and work-related uses more heavily,” the report said.

Despite rapid progress in generative AI since late 2022, the study found that actual adoption remains far below what current models could theoretically perform.

“AI is far from reaching its theoretical capability: actual coverage remains a fraction of what’s feasible,” the authors wrote.

The report also examined labour market trends since the emergence of generative AI tools and found limited evidence so far of widespread job losses in highly exposed occupations.

“We find no systematic increase in unemployment for highly exposed workers since late 2022,” the report said.

However, the researchers noted early signs that hiring dynamics may be shifting, particularly for younger workers entering the workforce.

“There is suggestive evidence that hiring of younger workers has slowed in exposed occupations,” the report said.