Sometimes the great verities are pretty straightforward. For example, “If something cannot go on forever, it will stop,” an observation made famous by economist Herb Stein. Let’s stick with that one, given its sensible application to the Trump administration’s current quasi-licensing regime for frontier AI models. The effort has proven to be a vibey, ad hoc process that The Economist correctly describes as “opaque, unpredictable—and unsustainable.” Good news that a more structured process apparently is coming soon.
The Financial Times reports that, as early as this week, the White House will roll out “voluntary standards for the release of new models” that would “set benchmarks for models with cutting-edge cyber capabilities and establish release timelines in an effort to streamline future launches.” What’s more, the guidelines would clarify “who is able to access advanced models, both domestically and abroad, in a move that could set the stage for a global framework including US allies.” Definitely seems less haphazard, I’ll give it that.
And that would be no small improvement. Policy uncertainty can be an important factor in economic performance. A 2025 analysis by the Penn Wharton Budget Model estimated that the increased uncertainty surrounding President Trump’s tariff announcements would reduce business investment by more than 4 percent for the year.
Uncertainty can also shape policy choices that seem far less momentous than those affecting global trade. A recent study by AEI economist Michael Strain and colleagues found that after the BLS boss was dismissed in August 2025 amid unfounded allegations that employment data had been manipulated, the resulting erosion of confidence in federal statistics increased economic policy uncertainty, “with existing estimates linking uncertainty to macroeconomic outcomes implying that the resulting loss of confidence may have reduced US GDP by roughly $20 billion.”
It’s hardly a leap to imagine that uncertainty over the regulatory approval process of a technology as hyped as generative artificial intelligence would carry all manner of downsides, including delayed investment, slower customer adoption, and even geopolitical risk. And although some plan may generally be better than no plan, to paraphrase former US Treasury Secretary Timothy Geithner, an affirmatively good plan would be preferable. Such a plan for frontier models might be built around a system of transparent, industry-run oversight that is government-supervised—as is the case with the financial industry—and that at all costs avoids a powerful government regulator micromanaging a fast-evolving technological revolution. We’ll see what exactly we get.