About
About the project
City AI Governance Project is an applied policy project focused on AI governance capacity in public institutions. It helps local governments ask better questions before adopting AI systems and studies the practical bottlenecks that shape responsible AI deployment.
The project studies how local governments develop the ability to inventory, procure, evaluate, oversee, and contest AI systems before deployment. Local governments face a distinctive version of the AI governance problem. They rarely build systems themselves; they acquire them through procurement, inherit them through vendor updates, and encounter them through staff adoption. Their decisions directly affect residents' benefits, permits, records, and interactions with public safety. And they must do all of this with limited specialized staff.
The materials on this site — the inventory template, procurement checklist, risk tier classifier, state guides, and readiness assessment — are designed to be adapted by any city, regardless of size, and to work within existing administrative structures: procurement offices, city attorney review, records management, and council oversight.
This project is not a vendor, law firm, or lobbying organization. It is a public-interest policy and research project. The focus is on implementation capacity: inventories, procurement review, risk classification, public transparency, human review, incident response, and resident accountability.
Working principles
Practical over aspirational
Tools a city can adopt this quarter with existing staff, not frameworks that require new agencies.
Nonpartisan
AI governance in local government is an administrative competence question, not an ideological one.
Capacity before deployment
The right time to build oversight is before systems are in production, when changes are cheap.
Research-informed
Materials draw on documented deployments, procurement records, and published evaluations of public-sector AI.
Project leadership
Founded and maintained by Jay Muñoz
Biography pending owner review. The site owner will add a concise biography here using verified affiliations and background. Until then, this section is deliberately left with placeholder text rather than invented credentials, employers, or partnerships.
Research and source methodology
- · State-guide legal claims are drawn from official state statutes, regulations, and agency guidance.
- · Recommendations are clearly distinguished from binding requirements.
- · Pending or inactive legislation is labeled separately from enacted law.
- · Each published state guide displays a source-verification date.
- · Corrections and newer official sources are welcome — please get in touch.
Work with us
We run closed working sessions for city leadership teams and collaborate with public agencies and policy organizations on AI governance capacity. The project is not a vendor, law firm, or lobbying organization.
Get in touch