Month ending September 30, 2026 Last updated October 12, 2026

Placements for jobs less impacted by AI are holding up better than others since the introduction of Chat GPT

Placements across the U.S. staffing market are down overall since January 2023, but the jobs involving the fewest tasks impacted by AI, roles like truck drivers and mechanics, have only declined 13%. More highly affected jobs, like data entry keyers and customer service representatives, are down 17-18% in that same time period. There was a bit of a reversal in September, but the longer term trend remains pronounced.

Jobs most heavily impacted by AI, where AI is automating or changing a large percentage of their tasks, represent a marginally smaller percentage of all the placements made over that time period. However, the shift is modest and does not yet suggest the widespread loss of jobs because of AI.

Age effects show a similar pattern: workers 25 years and younger represent a smaller share of placements in high-impact roles in most months.The reason could be twofold: fewer entry level roles are available, and the roles that remain are increasingly being filled by more experienced candidates. Automation may also be eliminating more routine work, raising the skill level required for the jobs that remain. However, the shift so far remains relatively small.

With hands-on work showing the biggest growth in placements and administrative and design work showing relative declines, the pattern suggests automation risk is shaping hiring trends, though other economic factors may also be at play. Early identification of which job groups are at risk, which are growing, and how skill requirements are shifting enables targeted reskilling and recruitment strategies before there is widespread displacement.

It will be interesting to track this data over time and see how these impact segments diverge or converge as AI replaces some roles and transforms the requirements of others.

Methodology

The ASA AI Impact Index combines Anthropic’s AI usage data with O*NET occupational task data to measure AI’s impact across job categories. The analysis identifies which tasks within each occupational group are being performed by AI, weights those tasks by their importance and frequency within the role, and categorizes job groups into impact levels based on the aggregate proportion of task performance. Bullhorn combines ASA’s AI exposure values with placement data from our flagship ATS product for customers opted in for data aggregation.

For proportion/ratio analyses, customers were qualified if they created placements within all three exposure categories / both age groups, and the average value per customer was calculated per period. For placement indices, customers were qualified if they created placements within the exposure category throughout the entire period. The average indexed value is given per customer group.

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