How State Lawmakers Are Using AI to Research, Fact-Check, and Draft Legislation

Statehouses must process more information with fewer people. In South Dakota, 70 part‑time legislators share roughly 60 staffers, the thinnest legislative staff in the country. [2] In that context, AI that can summarize documents, search regulations, and draft language looks like basic infrastructure, not a novelty.

Modern bills are long, technical, and often shaped by language supplied by interest groups. [3] Generative models now function as “synthetic staffers,” assembling intricate statutory text in minutes instead of days.

This is no longer hypothetical:

• In 2023, Representative Ted Lieu used ChatGPT to write a federal resolution on AI. [1]
• Federal agencies, including the U.S. Department of Education, have tested AI in regulatory drafting. [1]
• The Trump administration has reportedly eyed tools such as Gemini for transportation rules. [1]

📊 Key takeaway: AI is already embedded in U.S. lawmaking; the question is how to channel it responsibly, not whether it should exist.

Younger, wealthier, more Democratic-leaning states introduce the most AI-related bills, suggesting that digital capacity and political appetite move together. [6] This article surveys why legislatures turn to AI, how they use it, and what guardrails are needed.

Why State Legislatures Are Turning to AI

Part-time legislators juggle multiple roles with limited staff. Kent Roe in South Dakota, for example:

• Works as a farmland appraiser
• Serves on a utility board and church council
• Spends up to 40 days a year legislating, with minimal research support [2]

For officials in this position, tools that can instantly summarize a 200‑page report or draft an amendment determine whether they can keep up.

Key pressures driving AI uptake:

• Complexity of statutes: Modern laws can span hundreds of pages and reflect specialized lobbying input. [3]
• Lobbyist dominance: Lobbyists often supply pre-written fragments, exemptions, and carve-outs because lawmakers lack time to draft them. [3]
• Capacity gap: AI promises to restore some drafting power to legislators and nonpartisan staff, potentially broadening who can participate in drafting.

💼 Key point: When internal capacity is thin, external influence—often lobbyists—fills the gap. AI offers another source of drafting labor, but not a neutral one by default.

Normalization is accelerating: after Lieu’s AI resolution, agencies and states (including Virginia) began testing AI for review and drafting. [1] States most active in AI legislation—young, rich, Democratic-leaning—are also best positioned to adopt AI internally, creating a feedback loop. [6]

How Lawmakers Use AI for Research, Fact-Checking, and Drafting

Generative tools are being piloted in:

• The U.S. House and Senate
• Foreign legislatures
• Local governments, including a Brazilian municipality that passed the first known AI-written law in 2023 [3]

Common uses include:

• Searching databases and summarizing hearings
• Analyzing policy options
• Drafting bill sections and amendments [3]

Staff increasingly use AI for targeted recall rather than free-form drafting. One Midwestern staffer, for example, fed prior committee transcripts into an assistant to see how “short-term rental” had been defined in past debates, saving hours. [3]

Specialized “regulatory operating systems” are emerging:

• Vulcan Technologies aggregates statutes, regulations, and court decisions across governments. It can analyze legal language, answer queries, generate draft guidance, and propose text with citations. [1]
• Virginia has mandated Vulcan’s use across agencies to review and streamline rules, aiming to cut one-third of regulations. [1]

💡 Key takeaway: The frontier is shifting from generic chatbots to domain-specific legal copilots fluent in statutes, agencies, and case law.

Given the scale of regulation—the Code of Federal Regulations exceeds 200,000 pages across 200 volumes [4]—AI, with careful prompting and oversight, can:

• Identify regulations linked to particular statutes or sections
• Map relationships between rules, agencies, and enabling laws
• Answer questions like “How many regulations reference 44 U.S.C. §§ 3501–3521?” [4]

For investigations and oversight, generative systems can:

• Synthesize large evidence sets and cluster facts
• Flag inconsistencies and possible misinformation
• Support due diligence and monitor legal or regulatory changes over time [7]

They can draft timelines and highlight gaps, but outputs must be checked against the record. [7]

Professional platforms like CoCounsel Legal now integrate research, document analysis, and drafting into one workflow, reporting about 98% accuracy on supported tasks. [8] Adoption of generative tools among legal professionals rose from 14% in 2024 to 26% in 2025, signaling similar integrated tools for legislatures. [8]

Risks, Oversight, and Best Practices for AI-Assisted Lawmaking

AI-written law raises constitutional as well as technical issues. Cheap, detailed drafting lets legislators:

• Write more prescriptive statutes
• Narrow the discretion of executive agencies that traditionally flesh out vague laws through rulemaking [3]

⚠️ Key point: Faster drafting can quietly reshape separation of powers by hard-coding more policy detail into statutes. [3]

Quality risks include hallucinations, omitted caveats, and misstated precedent. [7] Responsible use requires workflows where:

• Outputs are treated as hypotheses, not facts
• Every substantive claim is checked against primary sources
• Citations and cross-references are systematically verified [7]

Verification must rely on lateral reading:

• Ask “who can confirm this?” not “who wrote this?” [5]
• Break responses into discrete claims
• Check each claim against trusted legal databases, government publications, and reputable analyses [5]

Statehouses should adopt policies that:

• Require disclosure when AI substantially contributes to bill text
• Set minimum human review standards before introduction
• Vet tools for ethics, security, and data governance
• Provide training that pairs technical skills with critical evaluation and lateral reading practices [5][8]

States already leading on AI bills are well-positioned to pilot governance frameworks for AI-assisted lawmaking, using early policy experience to guide transparent, accountable internal use. [6]

Conclusion: Treat AI as an Assistant, Not a Ghostwriter

AI is rapidly embedding itself in state-level lawmaking—from navigating the 200,000‑page CFR to analyzing evidence and drafting statutory language. [1][4][7] The benefits are speed and depth; the dangers are opacity, overreach, and subtle error.

Legislative leaders should map where AI is already used, set review and disclosure rules, and train staff in verification disciplines like lateral reading. [5] AI should function as a visible, accountable assistant whose work is always checked, attributed, and subject to democratic scrutiny.