Anthropic research finds skilled trades least affected by job loss to AI

Anthropic, an artificial intelligence company, has released new research stating that skilled trades are among the least at risk for job loss to AI.

According to its research, Anthropic determined that business/finance and sales are the highest occupational areas where AI is currently used. Installation/repair and transportation stand at nearly zero.

Workers in the most exposed professions are more likely to be older, female, more educated, and higher-paid, according to Anthropic.

It found that a job’s exposure is higher if:

• • “Its tasks are theoretically possible with AI;
  • “Its tasks see significant usage in the Anthropic Economic Index;
  • “Its tasks are performed in work-related contexts;
  • “It has a relatively higher share of automated use patterns or API implementation; and
  • “Its AI-impacted tasks make up a larger share of the overall role.”

The report states that the top 10 most at-risk jobs are currently:

1. 1. Computer programmers
   2. Customer service representatives
   3. Data entry keyers
   4. Medical record specialists
   5. Market research analysts and marketing specialists
   6. Sales representatives in wholesale and manufacturing, except for technical and scientific products
   7. Financial and investment analysts
   8. Software quality assurance analysts and testers
   9. Information security analysts
   10. Computer user support specialists

“At the bottom end, 30% of workers have zero [AI] coverage, as their tasks appeared too infrequently in our data to meet the minimum threshold,” the report states. “This group includes, for example, cooks, motorcycle mechanics, lifeguards, bartenders, dishwashers, and dressing room attendants.”

Anthropic says its research follows a “task-based approach, incorporating measures of theoretical AI capability and real-world usage, before aggregating to occupations.”

“Why might actual usage fall short of theoretical capability? Some tasks that are theoretically possible may not show up in usage because of model limitations,” the report states. “Others may be slow to diffuse due to legal constraints, specific software requirements, human verification steps, or other hurdles.”

Anthropic notes that 97% of the tasks observed across four previous Economic Index reports fall into categories rated as theoretically feasible.

“Theoretical capability encompasses a much broader range of tasks,” the report states. “By tracking how that gap narrows, observed exposure provides insight into economic changes as they emerge. Our measure qualitatively captures several aspects of AI usage that we think are predictive of job impacts.”

Anthropic shares an example of some worker characteristics in the top quartile of exposure and the 30% of workers with zero exposure in the three months before ChatGPT was released, between August and October of 2022.

“The groups are very different,” the report states. “The more exposed group is 16 percentage points more likely to be female, 11 percentage points more likely to be white, and almost twice as likely to be Asian. They earn 47% more, on average, and have higher levels of education. For example, people with graduate degrees are 4.5% of the unexposed group, but 17.4% of the most exposed group, an almost fourfold difference.”

Anthropic adds that it introduced a new measure of AI displacement risk — observed exposure, which combines theoretical large language model (LLM) capabilities and real-world usage data, weighting automated uses more heavily than augmentative and work-related uses.

“AI is far from reaching its theoretical capability: actual coverage remains a fraction of what’s feasible,” Anthropic wrote. “Occupations with higher observed exposure are projected by the BLS [Bureau of Labor Statistics] to grow less through 2034.

“We find no systematic increase in unemployment for highly exposed workers since late 2022, though we find suggestive evidence that hiring of younger workers has slowed in exposed occupations.”

Overall, Anthropic determined that AI’s labor market impacts, as tested against early data, show limited evidence that AI has affected employment to date.

“Our goal is to establish an approach for measuring how AI is affecting employment, and to revisit these analyses periodically,” the report states. “This approach won’t capture every channel through which AI could reshape the labor market, but by laying this groundwork now, before meaningful effects have emerged, we hope future findings will more reliably identify economic disruption than post-hoc analyses.”

Anthropic highlighted the COVID-19 pandemic’s impact on employment trends as a societal example of drastic economic change that spurred sudden technological advancements.

“Causal inference is easier when the effects are large and sudden,” the report states. “The COVID-19 pandemic and accompanying policy measures caused economic disruption so stark that sophisticated statistical approaches were unnecessary for many questions. For example, unemployment jumped sharply in the early weeks of the pandemic, leaving little room for alternative explanations. The impacts of AI, however, might be less like COVID and more like the internet or trade with China. The effects may not be immediately clear from aggregate unemployment data; factors like trade policy and the business cycle could cloud interpretations of trendlines.”

Anthropic concludes the report by noting that it plans to make several improvements to its research and that its AI usage data will be incorporated into future updates. It plans to continue “forming an evolving picture of task and job coverage in the economy.”

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Featured image: Anthropic logo provided by Anthropic