The impact of Artificial Intelligence on jobs has become one of the defining debates of the moment, according to major media. Anthropic has published a report titled 'Labour Market Impacts of AI: A New Measure and Early Evidence' based on its own real-world usage data, major media reports. The report introduces a new measure called 'observed exposure' to quantify which tasks are already being automated in practice.
According to Anthropic's research, AI has yet to trigger a wave of job losses. There is little evidence that AI has increased unemployment in the occupations most exposed to the technology since the launch of ChatGPT in late 2022, Anthropic states. However, entry into some highly exposed white-collar professions is beginning to slow, particularly for younger workers.
The rate at which workers aged 22 to 25 are starting new jobs in highly exposed occupations has fallen by roughly 14% compared with pre-AI levels, Anthropic reports. Analysis of US labour market data found no statistically significant rise in unemployment among workers in highly exposed fields, according to Anthropic. 3%), major media notes.
As capabilities advance, adoption spreads, and deployment deepens, the red area will grow to cover the blue. There is a large uncovered area too; many tasks, of course, remain beyond AI’s reach—from physical agricultural work like pruning trees and operating farm machinery to legal tasks like representing clients in court.
4%), and production (19%), major media reports. 8%, major media states. In computer and mathematical roles, current AI usage covers around a third of job tasks, Anthropic says.
Computer programmers, customer service representatives, and data entry workers are among the professions most exposed to AI tools, according to Anthropic. Workers in the most exposed occupations are more likely to be older, female, highly educated, and higher-paid, Anthropic reports. Around 30% of occupations show no meaningful AI coverage at all, including many hands-on jobs such as cooks, mechanics, bartenders, and lifeguards, Anthropic states.
Large language models remain far from reaching their potential impact across the economy, Anthropic notes. The gap between theoretical capability and real-world deployment may persist for years due to legal constraints, technical integration challenges, and the need for human oversight, according to Anthropic. How the 14% drop in job-finding rates for young workers in exposed occupations will affect long-term career prospects remains unknown.
The timeline for AI to reach its full theoretical potential across different occupational groups is also unclear.