July 14, 2026 Will Artificial Intelligence Broadly Raise Living Standards or Drive Income and Wealth Inequality? Governor Michael S. Barr At “Next-Gen Financial Inclusion,” the third annual Financial Inclusion Conference hosted by the Federal Reserve Board Share Watch Live I am grateful for the opportunity to speak to you. 1 Our focus in this conference is financial inclusion, and something that will likely have great consequences for financial inclusion and our economy more broadly in the years ahead is artificial intelligence (AI). As I have explored in a number of speeches over the past several years, AI has the potential to transform lives and the U.S. economy, possibly empowering workers to be more productive, with lower- and middle-income workers benefiting the most. 2 But it is also the case that AI may instead exacerbate inequality, eliminating some lower- and middle-income jobs while boosting the income and wealth of higher-income individuals. Since we don't know which of these futures will come about, it is useful to use potential scenarios, as I've done previously with respect to AI and the economy. Every major technological advance has had profound effects on labor markets and the economy. Many workers have suffered from these technological changes, while many other workers have seen new opportunities emerge. In the long run, technological advances tend to broadly raise living standards by creating more jobs than they destroy and increasing productivity. But transitions and outcomes can vary, and in the period following the mass adoption of a general-purpose technology—such as electricity, the telephone, and internet-enabled personal computers—the number of people dislocated and the extent of the harm they may suffer can be large and persistent. Balancing those scales of costs and benefits involves examining whether the benefits are broadly shared or concentrated. Past experience has shown that technological leaps forward can raise living standards. But when the benefits are concentrated among relatively few people, technology can widen inequalities of income and wealth, especially during the transition period. Widespread adoption of the internet raised the productive capacity of our economy and broadly raised living standards, but it also likely exacerbated inequality because it benefited information-intensive jobs (such as accountants) more than other jobs (say, construction workers). The policy challenge is therefore not simply to observe the development and deployment of AI, but also, as a society, to consider policies related to AI and its effects on education, job training and workforce development, competition, tax policy, and other areas that allow the gains from AI to be shared across workers, households, and communities, rather than accruing to a small group of firms and investors. 3 Of course, these policies are not within the remit of the Federal Reserve but rather for other policymakers to consider and decide. The question I would like to consider today is whether AI will likely help narrow inequalities of income and wealth, supporting advances in financial inclusion, or widen those inequalities, undermining the recent gains in financial inclusion that we rightly celebrate today. Understanding Inequality Let's start with understanding income and wealth inequality. To understand income inequality, it helps to break income into its components. The largest component is labor income. Disparities in labor income across individuals reflect the supply of and demand for their skills, their productivity, and their time spent at work—all things that will be affected by AI. Income also includes earnings from capital and investments and, thus, includes the concentration of ownership in firms, such as AI companies. In 2024, the highest-earning one-fifth of U.S. households earned 52 percent of all income, and the bottom 20 percent earned only 3 percent. 4 In 2024, the United States was the sixth most unequal of the countries in the G20. 5 Wealth inequality is a function of the distribution of ownership of assets—land, goods, businesses, intellectual property, and other investment assets. The bottom one-half of U.S. households hold less than 3 percent of wealth, the top one-tenth hold 59 percent, and the top one-tenth of a percent hold 15 percent. 6 When returns from investments are reinvested, wealth naturally compounds. As a result, those who already own appreciating assets often see their wealth grow much faster than households that rely primarily on wages, widening the gap between the "haves" and the "have-nots." A central question is whether AI will expand opportunity by giving more people access to valuable skills and productive work, or whether it will reinforce advantages that are already concentrated among a smaller population. Inequality matters not just for workers today, but it is also closely connected with an important aspect of the American Dream—the expectation that in the future, our children will be able to make better lives for themselves, including through rising living standards. 7 How AI Could Widen Inequality Let me start with the possible ways in which AI could widen inequality. Automation and Labor Displacement First, AI could lead to labor displacement. Something that is at the top of mind for most people, especially younger workers, is the concern that AI could drastically reduce the demand for them. AI might disproportionately affect new entrants to the labor market. According to a well-known paper by Claudia Golden and Larry Katz, in some previous technological waves, the benefits have tended to improve outcomes for more-skilled and more-educated workers. 8 But in this scenario, AI could harm not only less-skilled workers, but also younger college-educated workers whose skills are more easily replicated by AI than in prior technological waves. Moreover, workers who use AI more intensely might gain the most, and workers who use the most advanced and expensive AI models might win out over those who use baseline models. In the Federal Reserve's most recent Survey of Household Economics and Decisionmaking, 43 percent of workers with a graduate degree reported using AI in the previous month, compared with 10 percent of workers with a high school degree or less. 9 The survey further found that workers who used AI were more likely to say that it would improve their careers than replace their jobs. Measures of exposure to generative AI also suggest that higher education and higher-paid workers are much more exposed to generative AI. 10 The consequences of these facts are not yet clear. If AI mostly substitutes for labor, then not being exposed to AI would be positive for such workers; however, if AI augments existing jobs, then workers not exposed to AI would be left behind. There is substantial uncertainty about how the labor market will evolve. As of right now, there has been little evidence of economy-wide job displacement from AI. 11 Yet there is some evidence that AI may have made job entry harder for young workers in some job categories. 12 Given both the history of major technological advances and how early we are in the timeline of AI adoption, it is important to consider the full range of possible future effects, including the potential for more widespread labor displacement. Potential Concentration Another concern is concentration. A high degree of market concentration has important implications for individuals' economic outcomes. We don't know how the market will evolve. At one extreme, competition and distributed innovation could lead to AI becoming a cheap and ubiquitous commodity. In this scenario, access is democratized and gains are widely shared. Start-ups and smaller businesses have access to state-of-the-art AI resources and can continue their role as a key source of innovative ideas, goods, and services as well as an important engine of job creation for the U.S. economy. But according to a 2025 paper by Anton Korineck and Jai Vipra, an important factor is that AI has some characteristics that have, in the past, reinforced concentration of market power. 13 Like other high-tech innovations, because AI depends on access to data, model improvements, and computing power, it benefits from economies of scale and scope. Greater data, model improvements, and computing power yield vastly greater intelligence and capabilities. The high return from this advantage helps explain the huge investments and concentration of AI investment in giant firms, which is why they are referred to as "hyperscalers." AI has another feature that seems to be driving ever-greater concentration of market power—the fact that AI itself is a powerful tool to train and accelerate development of new AI models. That is, AI improves its own research and development. While computing technology has always tended to support the market dominance of industry leaders, the extent of the advantage possessed by AI industry leaders may prove to be unprecedented. As a result of these forces, it is possible that a small number of AI firms may dominate the market and investment returns may accrue primarily to owners of AI. 14 In this potential future, wealth generation—and, to some extent, income generation for those workers who can benefit from access to AI resources—could increase. But less access to ever-improving AI resources for most other firms and their employees would mean slower productivity growth for them, and a steadily widening gap between them and the firms and their employees with more access. As I said at the outset, I am not predicting this particular outcome, just exploring it as a possible scenario. How AI Could Alleviate Inequality Let me turn to scenarios in which AI could reduce inequality. AI as a Productivity Tool One scenario is broader access to capability building, resulting in broader productivity gains. Just as the printing press democratized knowledge and the internet democratized i
