A bipartisan group of senators is advancing legislation that would require the federal government to collect more detailed information about how artificial intelligence is changing the workplace. The bill’s sponsors argue that policymakers need better data to prepare workers for an AI-driven economy rather than relying on speculation about automation’s effects.
The proposal, the AI Workforce Projections, Research and Evaluations to Promote AI Readiness and Employment (AI Workforce PREPARE) Act, was the focus of a hearing Wednesday (July 29) before the Senate Health, Education, Labor and Pensions Committee’s Subcommittee on Employment and Workforce Safety. Lawmakers and witnesses broadly agreed that the most immediate effect of AI is likely to be the transformation of job tasks and skill requirements rather than widespread job losses.
Subcommittee Chairman Sen. Jim Banks (R-Ind.), who introduced the legislation in December, said existing labor statistics do not adequately capture how AI is reshaping work.
“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, per a writeup in GovTech. He described improved labor market data as the first step toward helping workers develop the skills needed “in the AI economy.”
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 add AI-related questions to existing federal surveys to measure how employers are deploying AI and which occupations are most affected. It also would authorize the Department of Labor to hire AI specialists, establish an AI Workforce Research Hub, monitor worker transitions between AI-affected jobs, and develop benchmarks for identifying tasks that are likely to be automated and require worker retraining.
Hickenlooper, the panel’s ranking member, framed the legislation as an effort to improve the quality of policymaking rather than regulate artificial intelligence directly.
“Informed policy starts with good data,” he said, adding that he is also developing separate legislation to create regional partnerships among educators, industry and workforce organizations to expand AI-related credentials, apprenticeships and job training programs tailored to regional labor market needs. He said the PREPARE Act would improve forecasting of workforce needs and the strategies needed to respond as AI adoption accelerates.
Witnesses largely endorsed the bill’s emphasis on expanding labor market data while recommending additional measures to improve the government’s understanding of AI’s economic effects.
Carol Rogers, director of the Indiana Business Research Center, urged lawmakers to establish common definitions for measuring AI adoption so that policymakers can “compare apples to apples” when evaluating its workforce impacts.
Liya Palagashvili, director of the Labor Policy Project at George Mason University’s Mercatus Center, argued that AI measurement systems should remain “resilient across several possible futures.” She recommended linking employer survey responses with hiring and wage data to compare outcomes between AI adopters and non-adopters.
“Early evidence does not yet show broad AI-driven employment loss,” she said, noting that employment trends among younger workers in AI-exposed occupations are “more consistent with slower hiring than with layoffs.” She added that some hiring slowdowns predated the emergence of modern generative AI systems, suggesting broader economic factors may also be influencing labor markets.
Other witnesses argued that AI’s greatest workforce risks stem from changing career pathways rather than eliminating jobs outright.
Ken Clark, president and CEO of workforce investment organization EmployIndy, testified that artificial intelligence is reshaping far more jobs than it’s 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 “hollow out” midlevel positions by automating the work through which employees traditionally gain experience needed for advancement.
“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.
