The Behavioral Sufficiency Problem

<div> AI governance frameworks have become the dominant policy response to AI risk across government, defense, and commercial sectors. This paper argues that these frameworks suffer from a fundamental structural problem: they are modeled on human regulatory theory, which was never designed to operate without the cultural, social, and psychological infrastructure that co-evolved alongside human law. We term this the Behavioral Sufficiency Problem. </div> <div> <br> </div> <div> Using original empirical analysis merging the Oxford Insights Government AI Readiness Index 2024 with the AI Incident Database (1,362 incidents through February 2026), we find a statistically significant positive correlation between governance maturity and documented public safety AI incidents (r = 0.363, p = 0.021). This counterintuitive result reveals that governance primarily creates reporting infrastructure rather than preventing incidents. </div> <div> <br> </div> <div> We present two analytical lenses through which to understand the Behavioral Sufficiency Problem and show that both converge on the same conclusion: current governance frameworks are not sufficient to determine AI system behavior in high-stakes domains. We conclude with practical prescriptions for policymakers, deploying organizations, and AI developers. </div>