AI Policy & Safety
What Is AI Regulatory Capture? A Plain-Language Guide
Regulatory capture is an old problem in a new setting: the people writing AI rules increasingly depend on the AI industry to understand what they are regulating. Here is what that means, why it matters, and how to think about what comes next.
Key takeaways
- Regulatory capture happens when an industry shapes the rules meant to govern it, shifting outcomes away from the public interest and toward its own priorities.
- AI is especially vulnerable to capture because of extreme information asymmetry: regulators often have no choice but to rely on the industry itself for technical expertise and safety data.
- AI lobbying has surged dramatically, with more than 3,500 federal lobbyists (over one quarter of all federal lobbyists) reporting lobbying on AI issues at least once in 2025.
- Capture works through many channels beyond lobbying, including the revolving door between government and industry, narrative framing, ethics washing, and funding academic research.
- Resource imbalances between well-funded industry actors and under-resourced civil society groups mean the public interest is structurally underrepresented in most AI policy processes.
Imagine hiring a locksmith to design the city's security code, then asking that same locksmith to inspect every door in town. That is the core tension at the heart of AI regulatory capture, and it is not a hypothetical. It is the live political economy of one of the most consequential technologies in human history. Understanding this dynamic is the first step toward thinking clearly about who actually controls AI's future.