New research from Anthropic reveals how artificial intelligence is actually affecting jobs in the real world. The company analyzed usage data from its AI assistant Claude and found that while some professions are seeing increasing automation, many jobs remain largely untouched.
During the test, each job received a coverage score. A high score meant AI is already performing a measurable share of that role's tasks in practice, a low score meant the job is least likely to be replaced.
The Gap Between AI Capability and Actual Use In The Real World
According to the research, there is a large difference between what AI could theoretically automate and what companies are currently using it for. For example, AI systems could potentially handle up to 90% of tasks in administrative roles. However, real-world usage data shows that adoption remains far lower.
Even in technology-related fields (the sector most affected by AI so far), observed AI usage covers roughly one-third of job tasks. This suggests that large-scale job replacement has not yet occurred, despite rapid advances in AI tools.
Jobs That Already See AI Pressure
Computer programmers show 75% task coverage, the highest in the dataset. According to the research, Claude usage in coding is weighted toward full automation rather than productivity assistance.
Customer service representatives rank second. Core tasks in that role are increasingly appearing in first-party API traffic, which the researchers describe as companies routing work through AI pipelines rather than human agents.
Data-entry workers follow at 67% coverage. Financial analysts and office administrators also appear among high-exposure occupations, though real adoption in administrative roles still trails theoretical capability.
The Bureau of Labor Statistics data cited in the research shows that for every 10 percentage point increase in a job's AI coverage score, projected employment growth for that role drops by 0.6 percentage points through 2034.
30% of U.S. Workers Cannot Be Replaced by AI
Approximately 30% of U.S. workers score zero. Their tasks do not appear in AI usage data at any meaningful level.
The research identifies these as roles dependent on physical presence, sensory judgment, and real-time situational reading. Zero-exposure occupations listed in the study include cooks, motorcycle mechanics, lifeguards, bartenders, dishwashers, agricultural workers, and courtroom lawyers.
The Bureau of Labor Statistics projects steady growth for blue-collar roles through the decade. Healthcare is adding roughly 40,000 jobs per month, according to the research, with demand for nurses, therapists, and care workers running ahead of AI displacement in those fields.
AI Impact May Affect White-Collar Roles The Most
One surprising finding is that the workers most exposed to AI tend to be older, highly educated, and higher paid. Researchers found that employees in AI-exposed roles earn roughly 47% more than those in jobs with zero exposure.
This differs from previous automation waves, which often affected lower-wage jobs first. Instead, AI appears to be targeting tasks commonly found in office-based professions.
Hiring Trends May Already Be Shifting
Although the research found no major rise in unemployment, early signs of change are appearing in hiring patterns. Among workers aged 22 to 25, the rate of finding jobs in AI-exposed occupations has dropped by about 14% since the release of ChatGPT in late 2022.
Researchers say this could indicate that companies are slowing hiring in roles where AI tools can already assist with key tasks.
What The Findings Mean For People
The data suggests that AI is reshaping tasks rather than eliminating entire professions. Roles that depend on physical skills, human interaction, or real-world environments appear far more resilient.
At the same time, office-based professions that rely heavily on digital workflows may continue to face growing automation pressure as AI tools become more capable.
Anthropic describes the index as a first step and plans to update coverage measures as usage data changes.
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