WASHINGTON — A bipartisan group of senators is advancing legislation aimed at giving policymakers a clearer picture of how artificial intelligence is reshaping the U.S. workforce, arguing that better data is needed to prepare workers for an economy increasingly influenced by AI.
The AI Workforce Projections, Research and Evaluations to Promote AI Readiness and Employment, or AI Workforce PREPARE Act, was the subject of a July 29 hearing before the Senate Health, Education, Labor and Pensions Committee’s Subcommittee on Employment and Workforce Safety. According to GovTech’s coverage of the hearing, lawmakers and witnesses largely agreed that AI is more likely to transform jobs and skill requirements than eliminate large numbers of positions outright.
Subcommittee Chairman Sen. Jim Banks (R-IN), who introduced the legislation in December, said existing federal labor statistics do not adequately measure AI’s impact on occupations and workforce trends.
Where Labor Statistics Fail
“Existing labor statistics too often fail to tell us how occupations’ tasks are changing, what skills are needed, which jobs will grow and shrink and how workers move through the labor force because of AI,” Banks said during the hearing, according to GovTech.
The legislation, co-sponsored by Sens. John Hickenlooper, D-Colo., Maggie Hassan, D-N.H., Jon Husted, R-Ohio, and Roger Marshall, R-Kan., would require the federal government to collect more detailed information on AI adoption and its effects on workers.
Key Provisions
Among its provisions, the bill would:
- Add AI-related questions to existing federal employer and workforce surveys.
- Track how employers are deploying AI and identify occupations most affected by the technology.
- Authorize the U.S. Department of Labor to hire AI specialists.
- Create an AI Workforce Research Hub.
- Monitor worker transitions into and out of AI-affected occupations.
- Develop benchmarks for identifying job tasks that are likely to be automated and where worker retraining may be needed.
Hickenlooper, the subcommittee’s ranking member, said the legislation is designed to improve policymaking rather than regulate artificial intelligence.
“Informed policy starts with good data,” he said, adding that he is developing separate legislation that would support regional partnerships among educators, employers and workforce organizations to expand AI-related credentials, apprenticeships and training programs.
Witness Statements
Witnesses generally endorsed the legislation while suggesting additional ways to improve the government’s understanding of AI’s economic effects, including:
- Carol Rogers, director of the Indiana Business Research Center, urged lawmakers to establish standardized definitions for measuring AI adoption so policymakers can consistently compare its effects across industries.
- Liya Palagashvili, director of the Labor Policy Project at George Mason University’s Mercatus Center, said AI measurement systems should remain flexible enough to accommodate multiple future scenarios. She recommended linking employer survey responses with hiring and wage data to better compare outcomes between businesses that adopt AI and those that do not.
- Palagashvili also said current evidence does not indicate widespread AI-driven job losses. “Early evidence does not yet show broad AI-driven employment loss,” she said, noting that employment trends among younger workers in occupations most exposed to AI suggest slower hiring rather than widespread layoffs.
- Ken Clark, president and CEO of workforce development organization EmployIndy, told lawmakers artificial intelligence is changing substantially more jobs than it is replacing. “The greatest long-term workforce risk is not widespread unemployment,” Clark said. “It’s the disruption of career pathways that workers rely on to gain experience and continually develop new skills throughout their careers.”
- Justin Heck, senior director of research and data production at Opportunity@Work, warned that AI could erode traditional career ladders by automating many of the intermediate responsibilities that help employees develop into future managers and leaders. “A company that automates the demanding parts of jobs may see short-term efficiency gains while inadvertently dismantling the pipeline that produces its own future supervisors and managers,” Heck said.
