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How Taxing AI Could Save Jobs
Advice for policymakers and large employers, who will be enlisted in minimizing job losses.
- By
- September 28, 2026
- CBR - Public Policy
AI-related job displacement is coming, though no one knows how fast it will proceed, how far it will go, and which sectors it will affect most. Much depends on the pace at which individual firms apply the technology to their operations.
Data from the US Census Bureau’s Business Trends and Outlook Survey indicate that, as of this past May, only 20 percent of firms with fewer than 20 employees were using artificial intelligence, compared with 37 percent of those with at least 250 employees. While larger companies were doing more with the technology, even 37 percent seems scant considering the survey’s low threshold for answering in the affirmative (whether AI is used “in any business function”).
For now, adoption is impeded by the difficulty of integrating already astonishing AI capabilities into existing workflows in a way that will allow companies to reap the benefits fully. At a minimum, successful integration requires models that are not only trained on existing data but also adaptive to new data generated through everyday use.
Another factor inhibiting adoption is uncertainty about cost. Many large companies are still running pilots and postponing hiring or firing decisions as they await more clarity. Eventually, however, competitive pressures will force them to adopt the technology more fully.
The outlook for jobs is not entirely pessimistic. If companies continue producing their current slate of goods and services, AI adoption will have the effect that any new technology has. Yes, some jobs will be rendered redundant, but some jobs will be made more productive and exciting as AI removes drudgery and assists with tasks humans do less well. And new jobs will be created, such as AI engineers who supervise the technology’s implementation.
Moreover, if AI adoption occurs because of the productivity increases it brings—rather than because it costs less in taxes than human effort—firms’ ability to produce more for less will allow them to reduce prices and increase sales. This is the famous Jevons effect: the greater sales should also increase jobs.
Yet another reason for optimism is that AI may help create new businesses. Jill might hesitate to become an entrepreneur selling driftwood furniture pieces because she needs a web programmer and an accountant to start up. With AI performing both those roles, perhaps she can set up a sole proprietorship at significantly less cost. The number of startups rose significantly during the pandemic and has increased further in recent quarters. Could AI accelerate this trend?
Recognizing that the first round of AI displacement will not be the last, it will be even more valuable to get firms to retrain workers periodically, and to retain workers whenever possible.
As MIT’s David Autor points out, AI can also equip certain workers with higher-order skills, as in the case of a nurse practitioner who can diagnose and treat many more illnesses with the help of medical AI. Given the enormous demand for medical services worldwide, and also services more generally, there is plenty of room, too, for job creation.
But even if the job apocalypse turns out to be less severe than many fear, minimizing its effects is still necessary to maintain social solidarity, and corporations will need to be enlisted in the effort. After all, they will have the best sense of the new opportunities that their employees can retrain for. The first task for any government, then, is to identify and address all the ways the tax system biases corporations against human labor. For example, a US firm contributes social security payments for every worker, but not for AI.
In a world where governments are already cash-strapped, one way to level the playing field is to levy a tax on the AI tokens a firm uses. The precise tax rate will need to be calculated carefully to avoid impeding AI deployment, but it can be set low initially and then gradually raised with experience. And in the United States, foreign providers will have to be brought into the net, as payments made to them aren’t as easily trackable as those made to domestic AI providers, though this is not an insoluble problem.
Recognizing that the first round of AI displacement will not be the last, it will be even more valuable to get firms to retrain workers periodically, and to retain workers whenever possible. Perhaps governments could consider a tax credit for additional training provided to workers, with one-third of the value usable each year that a worker retains employment (and not necessarily with the firm that provided the latest training). If the government wants to apply such a policy to AI adopters, it could even require the credit to be used only to offset the token tax.
More important than tax incentives, however, will be firms’ acknowledgement that they are fully engaged in helping their employees cope with an uncertain future. As questions grow about employment, even the best and brightest may worry about accepting offers from an employer who could fire them whenever it finds that AI can do almost as well, for less money. Employers who promise to support their employees may ultimately enjoy an additional bonus: As their reputation grows, they will have a wider pool of high-quality candidates to choose from.
The trend here is encouraging. In ongoing work, University of Miami’s Pietro Ramella (a former research professional at Chicago Booth), Booth’s Luigi Zingales, and I find that the share of Fortune 150 CEOs declaring in their letters to shareholders that they care about employee development increased steadily, from about 20 percent in 2008 to 44 percent in 2023. We cannot rule out the possibility that this is all cheap talk. One hopes not. The more that corporations engage in what may be the defining business challenge of our time—providing good jobs for humans—the more we can all look forward to a future of plenty.
Raghuram G. Rajan is the Katherine Dusak Miller Distinguished Service Professor of Finance at Chicago Booth. Copyright 2026 by Project Syndicate.
David Autor, “Applying AI to Rebuild Middle Class Jobs,” NBER working paper, February 2024.
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