ASA AI Impact Index Ranks Jobs Most Affected by AI Automation

How the index works

The tool is meant for staffing and recruiting professionals, who can use it to examine AI's effect on occupations and workplace tasks. It draws on data from Anthropic and the U.S. Department of Labor's O*NET. For each occupation, the index looks at the share of each task that is automated and augmented by AI.

Occupation-level measures are weighted by how important each task is to the job as a whole. According to the association, the result is a snapshot of AI's impact on tasks, occupations and broader segments of the labor market.

The ASA says the index will be released periodically, following the releases of the Anthropic and O*NET data.

Which jobs and groups are most affected

The initial results point to an uneven picture across industries and jobs. Among major occupation groups, computer and mathematical occupations show the greatest impact from AI automation and augmentation. Office and administrative support occupations come next, followed by sales and related occupations.

At the other end, construction and extraction occupations, farming, fishing, and forestry occupations, and production occupations show the least effects from AI.

At the level of individual jobs, three occupations are the most greatly affected by AI automation and augmentation:

• Software quality assurance analysts and testers
• Writers and authors
• Data entry keyers

The index also found 183 occupations with no automation or augmentation detected as of yet. Of these, 43 are in the construction and extraction occupations group.

What it means for staffing professionals

The ASA positions the index as a planning aid for the staffing industry. Noah Yosif, chief economist at the American Staffing Association, said: "In a sea of AI predictions, the ASA Impact Index allows hiring professionals a timely forecast of changes in labor demand based on what AI is taking off the plate of human workers."

He added that "Staffing and recruiting professionals can use the ASA Impact Index to anticipate client needs and position themselves as true workforce solutions partners."

Because the index rests on task-level data rather than broad predictions, it gives recruiters a way to see which parts of a job are changing. Since it will be updated as new Anthropic and O*NET data appear, the picture it offers is expected to shift over time.