Introduction

State legislative sessions are kicking into gear, and that means a flurry of AI laws are already under consideration across America. In prior years, the headline number of introduced state AI laws has been large: famously, 2025 saw over 1,000 state bills related to AI in some way. But as I pointed out, the vast majority of those laws were harmless: creating committees to study some aspect of AI and make policy recommendations, imposing liability on individuals who distribute AI-generated child pornography, and other largely non-problematic bills. The number of genuinely substantive bills—the kind that impose novel regulations on AI development or diffusion—was relatively small.

In 2026, this is no longer the case: there are now numerous substantive state AI bills floating around covering liability, algorithmic pricing, transparency, companion chatbots, child safety, occupational licensing, and more. In previous years, it was possible for me to independently cover most, if not all, of the interesting state AI bills at the level of rigor I expect of myself, and that my readers expect of me. This is no longer the case. There are simply too many of them.

It’s not just the topics that vary. It’s also the approaches different bills take to each topic. There is not one “algorithmic pricing” or “AI transparency” framework; there are several of each.

The political economy of state lawmaking (in general, not specific to AI) tends to produce three outcomes. First, states sometimes do converge on common legislative standards—there are entire bodies of state law that are largely identical across all, or nearly all, states. The second possibility is that states settle on a handful of legal frameworks, with the strictest of the frameworks generally becoming the nationwide standard (this is how data privacy law in the U.S. works). Third, states will occasionally produce legitimate patchworks: distinct regulatory regimes that are not easily groupable into neat taxonomies.