Actionable AI Insights for State Leaders

Clear, data-driven strategies to support AI adoption & empower policymakers.

Guiding State AI Policy with Data-Driven Insights

Artificial intelligence is everywhere—from shaping what we see online to influencing critical decisions in healthcare, finance, and beyond. But AI systems aren’t perfect. In fact, they are designed to use their imperfect nature to guide their learning, adaptation, and improvement over time. The real question isn’t simply how we build AI, but how we govern it responsibly—ensuring it works for people, not just for profit or efficiency.

At the Eagleton Institute of Politics, Dr. Michael Akinwumi is developing a co-intelligence approach to AI governance—a system that brings human expertise into the process of identifying and addressing AI risks. Making space for policy experts, scientists, and others to weigh in, shaping how AI operates in the real world.

Building on the foundation of the  MIT AI Risk Repository, Dr. Akinwumi’s AI oversight and policy engagement system organizes AI risks into categories and provides transparent explanations of why they matter. The system creates an opportunity for experts from science and policy fields to contribute their insights. Policy experts can then review recommendations informed by a broad range of subject-matter experts, refine strategies, and draft AI policies that can be implemented in the real world. This project is creating a pathway for meaningful human oversight, ensuring AI systems remain transparent, accountable, and aligned with the public interest.

As artificial intelligence continues to evolve, state governments face the challenge of developing policies that balance innovation, public trust, and societal impact. With a growing number of AI-related bills and initiatives, there is a critical need for evidence-based approaches to governance.

Launched by researchers at the Eagleton Science and Politics Program (Rutgers University), the State AI Preparedness (SAIP) Project provides objective, data-driven insights to support informed decision-making on AI policy at the state level.

SAIP Resources for State Leaders:

  • The SAIP Index – A structured tool for evaluating and benchmarking AI adoption in state governments.
  • AI Governance Frameworks – Policy models informed by survey data and machine learning to address state-specific needs.
  • Scalable Policy Approaches – Flexible strategies that adapt to varied state priorities while ensuring responsible AI implementation.
  • Guidance for Policymakers – Practical recommendations on oversight structures, technical assessments, and stakeholder engagement.
  • Interstate Collaboration – Comparative insights to facilitate knowledge-sharing and best practices across jurisdictions

Supporting AI Governance with Advanced Policy Mapping

Navigating AI legislation can be complex. The SAIP Index is a tool that provides policymakers with clear, structured insights into AI-related legislation. By analyzing bills across key sectors—housing, healthcare, and finance—the tool identifies policy issues, maps them to the MIT AI Risk Repository, and generates data-informed policy recommendations. The final output includes use case scenarios, offering practical guidance for AI governance at the state level.

Contributors & Collaborators

Itzhak Yanovinski is a professor at the School of Communication and Information at Rutgers University-New Brunswick

 

Michael Akinwumi is a Civic Science Fellow at the Eagleton Institute of Politics at Rutgers University-New Brunswick

 

Ojobo Agbo Eje  is a data scientist at Rutgers University-Camden

 

The State AI Preparedness Project