The dawning age of artificial intelligence holds great promise for the world economy and for the United States. Like so many other countries, the United States has endured decades of slow growth in labor productivity. Productivity, the amount of goods and services produced per worker, is the single most important measure of a country’s overall economic success. Slow productivity growth has meant poor growth in average incomes, which in turn has fueled much of the political turmoil manifested across the globe in the last generation. In the United States, slow growth in productivity has contributed to escalating political polarization and what many see as the gradual death of the American dream.

The United States needs to conjure up a productivity renaissance. And AI seems to be a perfect catalyst. In 2024, U.S. productivity in the nonfarm business sector grew by three percent, the fastest increase in a nonrecession, nonpandemic year in decades. A McKinsey study published in 2025 estimated that by 2030, AI-powered agents and robots could generate somewhere between $2.9 trillion and $6.4 trillion in new annual economic value for the United States—a productivity gain equal to nine to 20 percent of the country’s 2025 gross domestic product—and $28.7 trillion for the world overall.

AI is poised to power this kind of renaissance because it drives both capital investment and innovation, the two ways that countries can reliably increase their productivity. The United States and a growing number of other countries are witnessing a surge in capital investment in AI infrastructure, including computer chips, data centers, and electrical systems. According to the Federal Reserve Bank of St. Louis, AI-related investment accounted for about 39 percent of total U.S. GDP growth in 2025. That number is set to go up in 2026. According to the Financial Times, the four largest U.S. “hyperscalers” in AI and cloud computing—Alphabet, Amazon, Meta, and Microsoft—plan to increase their collective capital spending on AI in 2026 to $725 billion, a 77 percent increase from the roughly $410 billion they collectively spent last year.

The other means of increasing productivity, innovation, involves discovering new goods and services and more efficient ways to produce existing ones. Every day, companies are using AI to discover and take advantage of efficiencies and automate routine tasks. For example, AlphaFold, the AI program developed by DeepMind, whose scientists won the 2024 Nobel Prize in Chemistry, has dramatically quickened the discovery and analysis of the proteins needed to produce breakthrough drugs and other medical advances.

Yet despite all this economic promise, AI is also creating great political peril: the potential destruction of jobs at a faster rate and a wider scope than existing government assistance can reasonably address. This conundrum is hardly new. Innovation has almost always reduced labor demand for some goods and services. Sometimes that innovation did not result in widespread loss of existing jobs, but rather in the disappearance of old tasks and the invention of new tasks and capabilities within those occupations. In the early 1980s, for instance, around 16.5 million Americans worked in office operations and administrative support. Despite all the information technology inventions that have automated such secretarial tasks as taking dictation and making copies, almost the same number of Americans work in this sector today. They just do different things.

Sometimes, innovation permanently reduces demand for certain jobs: craftspeople producing horse-drawn wagons when the automobile was invented, typists with typewriters at the dawn of personal computers, workers on assembly lines automated with robots and other capital investments. This destruction is a fundamental feature of productivity growth. Indeed, the destruction of existing jobs, companies, and sometimes entire industries is a necessary condition for creating new jobs, higher incomes, and greater wealth.

But creative destruction also harms some workers and communities and can spark political resistance. This dynamic has been true since at least the Industrial Revolution, when the Luddites, skilled British textile workers protesting the invention and implementation of new machines, raided factories and destroyed power looms and knitting frames. Centuries later, the flood of low-cost Chinese exports into the United States reduced demand for many American-made goods, undercutting thousands of U.S. manufacturers and gutting many communities.

Today, evidence is building that AI is reducing labor demand in many industries, leading to an “AI shock” akin to the “China shock” of the early twenty-first century. But whereas the China shock was mostly confined to older workers in a few industries, the coming AI shock may ultimately prove much larger and more destructive. It is predominantly affecting the young rather than the old, the more educated rather than the less educated, and the full sweep of industries rather than mainly manufacturing. And because of the breakneck pace of innovation, the AI shock is reverberating much more rapidly than the China shock did.

AI is creating great political peril.

If the scope and speed of the AI shock exceed the capacity of policymakers to find solutions that blunt its negative effects, the repercussions may be severe. Countries that fail to institute adequate labor-market supports for displaced workers may lose out on the productivity gains of artificial intelligence if they bow to public pressure to pass new laws and regulations that stifle or even reverse its spread. They may face political turmoil along new, sharper cleavages. And they may fall permanently behind countries that manage to mitigate the AI shock and thus realize its full gains.

Some companies have taken welcome steps to help affected workers: Jamie Dimon, the chief executive and chair of JPMorgan Chase, and Dan Schulman, the CEO of Verizon, have each announced programs to assist employees whose jobs have been or will be eliminated because of AI. But private-sector solutions are insufficient to address AI’s economy-wide effects. Responding to the AI shock effectively requires meaningful public investment now. The United States is singularly unprepared for such an undertaking. Its antiquated labor-market policies are narrowly focused and inadequately funded. Without new sources of tax revenue to support and retrain displaced workers, the country will simply not be able to cope with the scale of the shock.

A pair of new policies can prevent the United States from repeating the mistakes of the China shock: tax credits to encourage training in new skills, and wage-loss insurance to encourage reemployment. These new fiscal outlays should be funded by a new tax on equity-related compensation, which would more fairly distribute the windfalls of AI’s expected productivity gains among the executives of companies that will financially benefit most from the technology’s disruptive effects and the workers hit hardest by it. The AI boom will assuredly transform the U.S. economy in ways no economist can fully anticipate. But these policies will ensure that its gains are more broadly shared across innovative companies, their workers, and communities across America.

DEGREES OF DIFFICULTY

Consider the following headlines from late 2025. In October, Amazon announced the elimination of 14,000 jobs along with plans for further cuts. A month later, Verizon eliminated over 13,000 jobs—roughly 13 percent of its workforce and its largest round........

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