Regulating AI in State Governments: Security Challenges and Legislative Responses

As artificial intelligence (AI) becomes embedded in state government operations, security risks, including data breaches, algorithmic bias, and adversarial AI, pose urgent challenges for policymakers. This study examines how U.S. states address AI security and identifies regulatory gaps using legislative analysis and a dyadic policy diffusion model. Results show AI policy adoption is driven by economic capacity and institutional professionalism, not geographic proximity. Despite expanding AI legislation, key security issues remain inconsistently addressed. The study proposes an Artificial Intelligence Secure Governance Framework informed by global best practices, emphasizing proactive governance, collaboration, and adaptive risk mitigation for public sector AI systems.