AI Trends for 2026: How States Will Shape AI Enforcement
As federal momentum toward a comprehensive U.S. AI law remains stalled, state regulators are stepping decisively into the gap. Heading into 2026, state attorneys general are likely to play an increasingly central role in shaping AI governance, not by waiting for new statutes, but by actively enforcing existing consumer privacy and AI-related laws.
Emerging Trends in AI Regulation
Two trends stand out in this evolving landscape:
- Use of Profiling Restrictions as a de facto AI enforcement mechanism.
- Expansion of a State-by-State AI Regulatory Patchwork.
Modern state privacy laws already provide regulators with a powerful hook. Many include limits on profiling, often defined as automated decision-making, particularly where such activities produce legal or similarly significant effects on individuals. In practice, these provisions give state attorneys general a ready-made framework to scrutinize high-risk AI systems.
Focus of Enforcement Actions
Enforcement actions are likely to first focus on familiar compliance failures, including:
- Inadequate or unclear notices.
- Missing or inoperative opt-out mechanisms.
- Discriminatory or biased outcomes.
- Ineffective or illusory appeals processes.
Rather than regulating AI specifically, state regulators can frame these cases as failures of consumer protection and privacy compliance. This approach allows state attorneys general to challenge algorithmic decision-making without needing to litigate the technical design or performance of the AI models.
The Fragmented Legislative Landscape
Simultaneously, the broader legislative landscape remains fragmented. There is still no realistic prospect of an omnibus federal AI or privacy statute in the near term. In response, states will continue proposing and enacting their own privacy and AI laws, but with a noticeable shift in emphasis. Following a December executive order signaling potential federal resistance to certain state AI regulatory approaches, lawmakers are likely to focus on areas viewed as less vulnerable to preemption or legal challenge, such as child safety protections.
For organizations operating across multiple states, the fragmented legislative landscape creates a familiar challenge. The patchwork of regulations will persist, and compliance will require careful mapping of AI use cases against overlapping privacy, consumer protection, and AI-specific requirements.
Managing Enforcement Risk
Enforcement risk will increasingly hinge on whether companies can demonstrate that they have:
- Identified high-risk uses.
- Assessed potential impacts.
- Implemented meaningful safeguards.
- Provided consumers with clear disclosures and workable remedies.
Looking ahead to 2026, companies should expect state attorneys general to be among the most active AI regulators in the United States. The absence of federal legislation has not resulted in regulatory silence. Instead, states will continue to adapt existing tools and enact targeted measures to shape AI deployment.
Organizations that treat profiling restrictions, transparency obligations, and appeals mechanisms as core components of AI governance will be better positioned to manage enforcement risk in an increasingly state-driven regulatory environment.
