“Trending” policy ideas tend to garner attention for all the wrong reasons: they seem like silver bullet solutions that will save us from taking on much harder reforms. Proposals to share profits from leading AI companies with the public are the latest example. It’s the rare policy scheme that seems to have united President Donald Trump, Senator Bernie Sanders, and CEOs at the leading AI labs. While the proposals for AI profit sharing vary in their precise details, a quick review of their likely outcomes should quickly deflate the popular excitement that has formed in response to calls for new taxes, public wealth funds, and the like. It’s important to reveal such limitations so that the AI policy discourse can move on to mechanisms more likely to address the real concerns of the American people.
In our first hypothetical world, the two leading AI labs—Anthropic and OpenAI—give away 3% of their equity. That’s not nothing! Based on current figures, such a contribution could kickstart a public wealth fund of about $55 billion. Let’s then imagine that fund earns 10% a year (a big “if” but let’s run with it). Per The Economist, this AI would reach a staggering $140 billion within ten years. How much would that benefit Americans? If annual payouts were 4% — what the publication reports is a proper amount to keep the fund going and growing — Americans would have an extra $20 in their pocket.
What if we taxed the companies? The Economist also did the math on an annual tax of 0.2% on the market value of AI companies, defined broadly to include AI labs as well as chipmakers. The result? At best, a few hundred dollars a year per American.
Yes, that’s it. Of course, such a fund or tax could be structured in a way that directed a greater share of those annual payouts to individuals from communities with particularly high rates of economic insecurity. But even with some reallocation of the funds, it’s obvious that this is not the AI policy to end all AI policy. In the optimistic case, it’s only ever going to be one of many policy interventions necessary to help Americans transition to the economy of the future.
That’s why it’s essential that these policies not be debated in isolation. Let’s assume that Congress managed to pass some fund or tax, there’s a risk that, given the outsized attention to this single idea, people would feel the temptation to end the economic transition effort there—problem solved, right?
Very unlikely.
The transition ahead will involve tackling a range of more complex, entrenched issues. There’s a clear need for occupational licensing reform so that more people can earn jobs in the care economy without being forced through credentialing programs that often have no tie to public safety. There’s an urgent demand for updating retraining programs that have consistently fallen short of their potential. And, there’s a whole range of barriers that need to be lowered to help more people start and sustain families.
Back-of-the-napkin solutions will not solve any of those issues. There’s no easy way through. Recognition of this challenge will help set expectations and make sure that success is not declared prematurely.
None of this means profit sharing deserves no place in the policy conversation. A modest fund or tax could help at the margins, and a thoughtful design could steer real support toward the communities facing the deepest insecurity. Yet the appeal of these schemes lies in their simplicity, and that simplicity is the tell. The home health aide blocked by needless licensing rules, the factory operator failed by a hollow retraining program, and the young couple priced out of starting a family will not be carried through this transition by a dividend of a few hundred dollars. The upshot is plain: profit sharing can be one tool among many, and the sooner we treat it that way, the sooner we get to the harder work that actually matters.
Kevin Frazier is the Director of the AI Innovation and Law Program at the University of Texas School of Law.
