The United States has no single federal AI law; instead, existing sector regulators (the FDA, banking supervisors, the EEOC, state insurance departments, and the FTC) apply their pre-existing authorities to AI systems case by case. This matters because a hiring algorithm, a diagnostic device, and a credit-scoring model each answer to a completely different regulator with its own vocabulary, timeline, and enforcement posture — there is no "AI compliance department" shortcut that satisfies all of them at once. The landscape is also unusually fast-moving in 2025-2026: several bedrock frameworks (bank model-risk guidance, EEOC hiring guidance, federal fair-lending enforcement) have been replaced or pulled back within the last eighteen months, even as state regulators, attorneys general, and private plaintiffs increasingly fill the resulting gap. Reading any real AI deployment correctly means identifying which sector regulator actually owns it, not assuming a horizontal framework like the EU AI Act has a US equivalent.
What This Cheat Sheet Covers
This topic spans 12 focused tables and 92 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
A jump-to index of every table row in this cheat sheet.
An interactive map of every table and concept in this topic.
Table 1: Mapping the US Sectoral AI Regulatory Landscape
Before diving into any one sector, it helps to see the whole map at once: which regulator owns which kind of AI decision, and why the US model looks nothing like a single horizontal AI statute.
| Regulator | Example | Description |
|---|---|---|
Clears an AI-enabled diagnostic imaging algorithm through the 510(k) pathway | Regulates AI/ML embedded in medical devices and drug development under the existing Food, Drug, and Cosmetic Act, not a new AI statute. | |
Issue joint supervisory guidance on a bank's AI-driven credit-scoring model | Oversee AI used inside banks through existing safety-and-soundness supervision, not consumer-facing rulemaking. | |
Applies ECOA adverse-action notice rules to an algorithmic loan denial | Enforces existing consumer-credit statutes against AI-driven lending decisions rather than issuing AI-specific rules. | |
Investigates a resume-screening algorithm for Title VII disparate impact | Applies decades-old civil-rights statutes to AI-driven hiring, promotion, and termination tools. | |
A state insurance commissioner adopts the NAIC's model bulletin requiring an insurer AI governance program | Insurance is regulated state by state; the NAIC coordinates model guidance that individual commissioners then adopt. |