Federal Reserve Board's Barr says AI's impact on inequality will depend on education, training and competition

Federal Reserve Board Governor Michael S. Barr, speaking at the Board's financial inclusion conference, discussed how artificial intelligence could either widen income and wealth inequality or support broader gains in living standards and financial inclusion. He framed the issue as uncertain and scenario-based, arguing that the distribution of AI's benefits will depend on how labor markets adapt, who gains access to the technology, and how policy choices shape the transition, particularly in education, job training, workforce development and competition. Barr said AI could worsen inequality if it displaces workers, especially younger or less advantaged entrants, or if the strongest gains accrue mainly to workers and firms with access to advanced AI tools. He also highlighted the risk that AI's reliance on data, computing power and self-reinforcing model development could concentrate market power and investment returns in a small number of large firms. At the same time, he outlined scenarios in which AI acts as a productivity tool that helps less-experienced workers, lowers barriers to entrepreneurship, broadens access to skills such as coding and creates new jobs, rather than simply replacing labor. He noted that recent Federal Reserve survey data showed much higher AI use among workers with graduate degrees than among workers with a high school degree or less, while also saying there is still little evidence of economy-wide job displacement from AI. Barr did not announce a new Federal Reserve measure. He said decisions on AI policy, education, worker training, competition, tax policy and related areas will help determine whether AI's gains are broadly shared, while noting that those policy choices fall to other policymakers rather than the Federal Reserve.