How Ai Helping States Cut Through Decades Red Tape

2026-07-23 · Source: siepr.stanford.edu · Field: Government & Public Sector — Digital Government & E-Government, Public Policy & Governance, Regulatory & Compliance · Depth: Intermediate, short

Summary

Stanford RegLab, led by SIEPR Senior Fellow Daniel E. Ho, developed an AI tool to analyze 500 million words of state statutes across all 50 U.S. states, identifying "policy sludge" like outdated reporting requirements and commissions. This research, detailed in a paper forthcoming in the Yale Journal on Regulation, revealed significant findings: reporting requirements in California grew by 400 percent from 2000 to 2025, many reports are never filed (30 percent in California), and costs vary dramatically, with one report consuming 3,500 staff hours and over \$870,000. While reporting requirements are more prevalent in Democratic states, the problem is widespread. The team collaborated with New York, California, and Maryland, leading to New York Gov. Kathy Hochul's Executive Order 61 for a "regulatory reset." The project also provides a model state statute for future regulation and a public website to explore state reporting requirements.

Key takeaway

For state and local policymakers aiming to improve government efficiency, you should consider adopting AI-powered statutory analysis to identify and eliminate "policy sludge." This approach, demonstrated by Stanford RegLab, can streamline operations, reduce civil servant burdens, and restore public confidence. Implement model statutes with automatic sunsetting and digital repositories to prevent future bureaucratic bloat.

Key insights

AI can efficiently identify and quantify "policy sludge" in state statutes, enabling governments to streamline operations.

Principles

• Bureaucratic bloat is widespread across U.S. states.
• Many mandated reports offer little value.
• Cost and impact data are crucial for reform.

Method

An AI system methodically scans 500 million words of state statutes to identify reporting requirements, commissions, and fees, converting legalese into digestible datasets for systematic review.

In practice

• Use AI to scan legal texts for obsolete provisions.
• Implement automatic sunsetting for new regulations.
• Create digital repositories for mandated reports.

Topics

• AI in Government
• Regulatory Reform
• Policy Sludge
• Statutory Analysis
• Government Efficiency
• Bureaucracy Reduction

Best for: Executive, Research Scientist, AI Scientist, Policy Maker, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by siepr.stanford.edu.