Artificial Intelligence in State Government Index
A public benchmark by Isaac Seiler measuring generative AI adoption, training, governance, pilots, transparency, and preparedness across U.S. states and territories.
Project Snapshot
- Project type: RESEARCH
- Year: 2025
- Primary topics: generative AI, state government, AI governance, public policy
- Search focus: AI state government index, public-sector generative AI adoption, state AI governance, training, pilots, sandboxes, and transparency.
Key Proof Points
- Built a 15-criteria GenAI Preparedness Score from publicly verifiable evidence.
- Benchmarked all U.S. states and territories on AI governance and adoption signals.
- Published state-by-state analysis with recommendations for lawmakers.
Overview
This work, published with the Council of State Governments, translates the GenAI hype cycle into a measurable picture of how state and territory governments are actually responding.
I built a public-information benchmark that scores all states and territories on concrete adoption signals including employee guidance, training, sandboxes, pilots, governance structures, and transparency, then paired the index with a policy roadmap for what leaders should do next.
The headline result was stark: most states scored below 50/100, and only a small handful cleared 80, suggesting the U.S. state landscape is early, uneven, and often opaque.
What I Built
- GenAI Preparedness Score: a 15-criteria scoring framework grounded in publicly verifiable evidence.
- Composite scoring: a weighted model combining preparedness with an efficiency adjustment.
- State-by-state analysis and rankings with concise synopses explaining each placement.
- A practitioner roadmap tied directly to observed policy, training, pilot, and transparency gaps.