Preparing for State-Level AI Regulation
In 2025, the landscape of AI and data privacy regulations is marked by uncertainty and inconsistency across the United States. With the change in administration, the regulatory focus has shifted dramatically, leading to a complex environment for businesses navigating compliance.
Policy Whiplash: A Shift in Direction
When President Trump took office, one of his initial actions was to revoke the previous administration’s Executive Order on AI regulation, replacing it with a directive aimed at deregulating AI development. This shift has resulted in a pendulum swing between regulatory guardrails and an emphasis on acceleration, leaving organizations grappling with the implications.
The growing disconnect between federal ambitions and practical compliance presents a daunting challenge for CISOs and governance, risk, and compliance (GRC) leaders. With federal regulatory bodies like the FTC and CFPB facing budget cuts and diminished authority, comprehensive federal data privacy legislation appears unlikely in 2025.
The Patchwork of State Regulations
Since 2018, attempts to unify the country’s fragmented state regulations have stalled, despite increasing pressure from the private sector for a cohesive standard. On the AI front, the failure of the House to impose a moratorium on state-level enforcement of AI regulations has shifted the regulatory spotlight to state legislatures, where a wave of privacy and AI bills are being introduced.
This state-driven regulatory environment is anything but uniform. Notable legislative efforts include:
- California AB 2930: This proposed bill mandates developers of automated decision systems to conduct impact assessments and notify users when these systems play a substantial role in consequential decisions.
- Colorado Artificial Intelligence Act SB 24-205: Enacted in 2024 and effective in 2026, this law imposes strict obligations on developers of high-risk AI systems, requiring transparency disclosures and measures to prevent algorithmic discrimination.
- New York AB 3265 – The “AI Bill of Rights”: This broad proposal includes consumer rights to opt out of automated systems and mandates human oversight in decision-making processes.
Additionally, while not a state bill, the EU AI Act introduces tiered risk classifications for AI systems, imposing varying compliance obligations that international organizations must navigate.
Navigating a Complex Compliance Landscape
For enterprise organizations investing heavily in AI, the lack of a clear regulatory map complicates compliance efforts. Companies must contend with overlapping and conflicting requirements from different states.
Best Practices for Compliance
To successfully navigate this uncertain regulatory climate, organizations can adopt the following best practices:
- Connect the Dots in the AI Stack: Achieving visibility into the data flow within AI systems is crucial. Understanding how sensitive data integrates into AI processes allows organizations to maintain compliance and enforce policy effectively.
- Bring Order to Unstructured Chaos: Unstructured data, often governed poorly, poses significant risks. Next-generation data security posture management tools can classify and safeguard sensitive information before it is ingested by AI models.
- Contextualize the Risk: Regulations are not just about compliance; they revolve around understanding the nuances of who, where, and why. Context-aware tools that create real-time knowledge graphs are essential for enforcing dynamic controls and adapting to evolving regulatory requirements.
Conclusion: The Road Ahead
The remainder of 2025 is likely to remain a regulatory gray zone for AI. Organizations must recognize the reputational and legal risks associated with noncompliance. Those that perceive AI governance as a mere checkbox will fall behind; conversely, those that integrate security, privacy, and compliance into a cohesive strategy will be better positioned to innovate responsibly.
As the regulatory landscape evolves, proactive engagement in AI and data governance is not just a best practice; it is essential for building trust and ensuring sustainable business operations amidst changing regulations.
