New York Governor Kathy Hochul has deployed artificial intelligence to conduct a comprehensive audit of every state rule, regulation, and policy, with the stated goal of identifying and eliminating outdated legislation. In an interview with Bloomberg’s Odd Lots podcast, Hochul detailed how her administration used AI to complete a review of the state’s entire legal code, a task she estimated would have taken a team of staffers five years to finish manually. The AI-driven analysis was completed in a matter of months, according to the governor.
How New York Is Using AI to Audit Its Legal Code
The initiative involves feeding the state’s extensive body of regulations into an AI system designed to flag provisions that are obsolete, contradictory, or no longer serve their intended purpose. The goal is not to replace human judgment but to dramatically accelerate the discovery phase of legislative cleanup. Hochul pointed to specific examples of antiquated laws unearthed by the analysis, including a $25 fee required to take a dog hunting and a requirement that pregnant individuals obtain a permit to work after midnight. These are the kinds of minor, archaic statutes that accumulate over decades and remain on the books simply because no one has the resources to find them all.
“Probably would have taken five years at the staff level” to review all the laws manually, Hochul told Bloomberg. “But with AI, we did it in a couple of months.” The speed of the audit allows the governor and state agencies to move quickly on removing these outdated regulations, a process she described as “getting rid of” the clutter in the state’s legal infrastructure.
The Timing: A Moratorium on AI Data Centers
The announcement of the AI-powered legal audit arrives alongside a distinctly cautious stance on the physical infrastructure powering such technology. Earlier this week, New York became the first state to enact a moratorium on new hyperscale data centers, pausing approvals for up to a year. State lawmakers plan to use this window to develop regulations aimed at protecting residents from rising utility costs and the environmental strain that massive data centers place on natural resources.
This dual approach—embracing AI as a tool for governance while pausing the buildout of its most resource-intensive hardware—presents a nuanced picture of how a major state is navigating the AI era. It suggests a willingness to deploy the technology for efficiency gains in public administration, coupled with a recognition that the industry’s physical expansion requires careful oversight.
What This Means for Government Efficiency
The New York initiative is a concrete example of a concept often discussed in theory: using AI to improve the efficiency and responsiveness of government. The sheer volume of existing rules in any large jurisdiction makes manual review prohibitive. Agencies typically lack the staffing to conduct a full audit of their own regulations, meaning outdated or conflicting rules persist for years, creating friction for citizens and businesses alike.
Hochul framed the effort in terms of reducing bureaucratic burden. “I want a government that’s not on your back but on your side,” she said. “And using AI has been powerful to do that. I think every level of government should use this… I’m going to make dramatic changes using the power of AI.” The statement signals an intent to scale the approach beyond this initial audit, potentially setting a precedent for other states and federal agencies looking to modernize their regulatory frameworks.
How the AI Review Works in Practice
While specific technical details of the AI system were not disclosed in the interview, the use case falls squarely within the capabilities of modern large language models and document analysis tools. An AI system suitable for this task would need to:
- Ingest and parse a vast corpus of unstructured legal text spanning multiple decades.
- Identify patterns that indicate obsolescence, such as references to defunct agencies, outdated fee structures, or laws that have been superseded by newer statutes.
- Cross-reference rules against current legal codes to detect contradictions or redundancies.
- Flag candidates for review by human experts who make the final determination on whether a rule should be repealed or amended.
The critical distinction here is that the AI is acting as a triage tool, not a decision-maker. It surfaces the most likely candidates for removal, dramatically narrowing the scope of work for human legal analysts. This is a pattern likely to be replicated across other government functions where the bottleneck is not judgment but the sheer volume of data to be reviewed.
AI for Governance: A Front-Line Use Case
The application of AI to regulatory review addresses a genuine pain point in public administration. For professionals and businesses operating in heavily regulated environments, the existence of obsolete or conflicting rules creates compliance uncertainty and unnecessary costs. An AI-assisted cleanup of the legal code can directly reduce this friction.
The approach is also notable for its relatively low risk profile compared to other government AI deployments. The AI is used for discovery and flagging, not for enforcement or adjudication. Human oversight remains central to the process, which mitigates many of the concerns around bias, accuracy, and accountability that plague more ambitious AI projects in criminal justice or benefits determination.
Who Should Pay Attention to This Development
This initiative is directly relevant to several groups:
- State and local government officials looking for a replicable model for regulatory modernization without massive new hiring.
- Legal professionals and compliance officers who work with New York state regulations and may see a reduction in outdated statutory requirements.
- AI and software vendors specializing in document analysis, legal technology, and natural language processing, as government procurement represents a growing market for these tools.
- Businesses operating in New York that could benefit from a cleaner, more predictable regulatory environment.
The New York example demonstrates that the value of AI is not limited to flashy consumer products or high-stakes scientific research. Sometimes, the most impactful application is the unglamorous work of cleaning up a decades-old database of rules so that a government can function more efficiently.
What to Watch for Next
The immediate next step is the actual repeal of the laws identified by the AI review. That process will require legislative action or agency rulemaking, depending on the type of regulation. The speed and effectiveness of this follow-through will determine whether the AI audit becomes a genuine success story or a well-publicized exercise that yields limited tangible change.
For readers and professionals observing this space, the key takeaway is the demonstrated feasibility of using AI for large-scale regulatory analysis. If New York follows through on its promise to “get rid of” the outdated rules it has identified, it will provide a powerful case study for governments worldwide. The technology is already capable of this work. The challenge now is the political and procedural will to act on the findings.
Anyone interested in this intersection of AI and governance should monitor how New York structures the repeal process and whether other states or federal agencies adopt similar methods. The potential for AI to streamline not just business workflows but the very legal frameworks that govern them is a development worth tracking closely.
