How States Are Shaping AI Laws Before Congress Acts

As artificial intelligence rapidly transforms industries and everyday life, state legislatures across the U.S. are stepping up to regulate where federal action has lagged. From employment screenings to facial recognition and algorithmic transparency, states are crafting their own legal frameworks to address AI’s far-reaching implications. These laws are setting important precedents and could influence eventual federal regulation.

The federal gap and state momentum

Congress has introduced several AI-related bills in recent years, but none have yet passed into comprehensive law. In the absence of overarching federal legislation, states have moved to fill the legal vacuum. This decentralized approach has led to a mosaic of AI regulations that reflect local priorities and political landscapes.

For example, Illinois’ Biometric Information Privacy Act (BIPA) has become a cornerstone for facial recognition law, imposing strict consent requirements and providing a private right of action. Colorado and California have also led the way with laws aimed at algorithmic fairness and consumer data protection. These efforts have sparked national conversations and served as models for other jurisdictions.

Emerging areas of legal focus

State-level AI legislation tends to focus on key areas where algorithmic decisions impact civil liberties and economic opportunity. One such area is employment. Maryland and New York City have passed laws requiring companies to disclose and audit the use of automated hiring tools. These regulations aim to reduce algorithmic bias and increase transparency in recruitment.

Another significant area is surveillance technology. Several states, including Virginia and Massachusetts, have restricted or outright banned the use of facial recognition by government agencies. These laws often reflect growing public concern over privacy and the disproportionate impact of such tools on minority communities.

In the education sector, states are beginning to address AI-driven tutoring, grading, and proctoring systems, seeking to ensure they do not compromise student rights or replicate inequities. As AI tools proliferate in public schools, legal scrutiny is expected to increase.

Legislative approaches and legal mechanics

States are using a range of legal mechanisms to regulate AI. Some have passed comprehensive frameworks, while others focus on narrow use cases. California’s proposed Assembly Bill 331, for example, would establish standards for automated decision systems, including mandatory impact assessments and data governance policies. Washington state has proposed a similar model with added provisions for government accountability.

Many state laws incorporate principles of explainability, fairness, and accountability. However, enforcement remains a challenge. Unlike traditional product regulations, AI systems are dynamic and opaque, making it difficult for regulators to assess compliance without specialized expertise. This has led to calls for state-level AI commissions or task forces to oversee implementation and advise on policy updates.

Implications for businesses and the public

For businesses, the patchwork of state AI laws presents both legal and operational challenges. Companies operating in multiple states must navigate different compliance requirements, especially when deploying AI tools that affect hiring, lending, or customer profiling. Some firms are responding by designing systems to meet the strictest state standards, effectively setting a de facto national benchmark.

Consumers stand to benefit from these regulations, particularly in areas where AI decisions can materially affect lives. State laws requiring disclosures, audits, or consent empower individuals with information and recourse. However, there is also concern that uneven regulation could create disparities in rights and protections depending on geographic location.

For legal professionals, this evolving landscape offers new frontiers in compliance, litigation, and public policy. Attorneys are increasingly advising clients on how to assess AI risk, draft internal policies, and engage with lawmakers on emerging legislation.

The path forward and future alignment

While state-level innovation in AI regulation is commendable, it also underscores the need for coherent federal policy. A national framework could establish baseline protections, prevent regulatory arbitrage, and streamline compliance. Until then, state laws will continue to serve as laboratories for experimentation and sources of policy innovation.

The next few years are likely to bring continued momentum at the state level, especially as AI tools become more integrated into essential services. Watching how these laws interact, conflict, or converge will be critical for policymakers, businesses, and citizens alike.

In the interim, the legal community has a unique opportunity to shape responsible AI governance by participating in public comment periods, advising on draft legislation, and educating clients about evolving risks and best practices.