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.
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.