Amidst all the flashy headlines of the integration of AI by tech companies resulting in massive layoffs. There is a sense of fear being created that all jobs that humans do will be taken over by AI. Although the IT sector witnessed mega layoffs owed to AI, people working in other industries often worry about which industry will AI come for next.
Anthropic, in this regard, recently published a study, and after analyzing 2 million conversations with its Claude AI model, it has highlighted a stark disparity between what AI could automate in jobs today and what it’s actually doing in the current market. The data from the study reveals which jobs are actually threatened by AI in the near future and which ones are far from any AI-related threat yet.
The study, titled “Theoretical Capability and Observed Usage by Occupational Category,” shares a chart that plots 22 sectors on a 0-1 scale. Out of all the listed jobs, computer and math top theoretical exposure at 94%, followed by office and admin at 90% and legal near 90%. Architecture and engineering, business and finance, and management jobs all exceed 60%.
However, the actual usage observed is far less than the theoretical prediction. The study observes just 33% in computers and math to be the highest, while most categories hover below 20%, per the Anthropic Economic Index. Physical roles like grounds maintenance, construction, and agriculture register near-zero on both.
Which jobs are going to be hit rapidly?
Anthropic’s “observed exposure” metric relies on real-world Claude interactions, prioritizing automation over augmentation. Top observed hits include computer programmers (75%) and data entry keyers (67%), but 30% of US workers show zero coverage due to infrequent task data. No mass layoffs have happened yet, but hiring for 22-25-year-olds has slowed 14% in vulnerable fields, favoring experienced staff.
Vulnerable workers skew older, female, educated, and higher-paid, flipping blue-collar disruption narratives.
What did the study mention on upskilling?
Anthropic attributes lag to model limits, workflow inertia, and regulations; predict accelerations as capabilities evolve. “AI is far from reaching its theoretical capabilities,” the report states, urging tracking via future economic index updates.
Experts add that white-collar roles face productivity booms or obsolescence. With 49 percent of US jobs now exposing over 25 percent of tasks to AI (up from 36 percent last year), adaptation is key.