Government AI Landscape Assessment

calendar_today July 2025

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Introduction

Artificial Intelligence is reshaping how public services are designed, delivered, and evaluated across the United States

The use of AI in the public sector brings immense opportunities—but also immense risks. That’s why we’ve created this Government AI Landscape Assessment to evaluate the readiness of U.S. state governments in responsibly adopting AI.

Code for America is dedicated to advancing the use of human-centered AI in government. We hope this Landscape Assessment provides the civic-tech community with a clear, actionable picture of how AI is transforming public service delivery. The rapid evolution of AI means that states are at varying stages of AI readiness.

The Landscape provides a comprehensive snapshot across key dimensions such as Leadership & Governance, AI Capacity Building, and Technical Infrastructure & Capabilities. Most states are navigating early or developing phases in these categories, building foundational capabilities while defining governance structures and strategic direction. But a few have emerged as national leaders—setting up dedicated AI offices, launching sophisticated pilot programs, training their staff, and building out infrastructure.

Reflecting a moment in time

This is a rapidly changing landscape. Our assessment was conducted in spring 2025 and published in July. States are making changes, implementing new programs, and piloting new tools that may not be reflected in this assessment.

Responsible AI in government

Like any technology, AI can do harm if it isn't stewarded responsibly. Read more about Code for America's approach to responsible AI in government.

Assessment dimensions

Leadership & Governance

Strong leadership and governance are foundational elements to effectively integrate AI across state agencies. This category evaluates the organizational structure and leadership dedicated to AI initiatives. It assesses whether there is executive-level ownership through a Chief AI Officer or equivalent position, the existence of a cross-agency AI advisory group, and an overall governance approach to AI implementation.

AI Capacity Building

All organizations are in learning mode as rapid technological evolution requires upskilling and education. This category evaluates the state’s investments in developing AI literacy, skills, and expertise across its workforce. It examines formal training programs, partnerships with educational institutions and industry for knowledge transfer, and structured upskilling pathways for employees.

Technical Infrastructure & Capabilities

Robust technical infrastructure is essential for successful AI adoption. This category evaluates the technical foundation necessary to support quality data and advanced AI implementations. It examines data infrastructure and accessibility, computing resources and platforms, and partnerships with technical vendors and service providers.

Readiness levels

Early

Initial steps in AI adoption with foundational elements beginning to emerge

Developing

Core components in place with growing capabilities and emerging formalization

Established

Mature implementation with systematic approaches and demonstrated effectiveness

Advanced

Sophisticated capabilities with comprehensive frameworks and innovative approaches

States may find themselves at different maturity levels across different categories, reflecting their unique strengths and focus areas. This variation is expected and can help identify where to concentrate resources for advancement.

The Road Ahead

The AI Road Ahead for State Government

State governments are poised for significant advancements in AI readiness over the next year, influenced by both industry developments and internal policy shifts. Here are some of the driving trends in the three categories.

Leadership & Governance

  • Federal initiatives: New executive orders on AI and further encouragement for efficiency gains may encourage more states to appoint Chief AI Officers and establish dedicated AI task forces.
  • Legislative action: States are enacting laws to regulate AI use in government, promoting transparency and ethical standards. For instance, New York's legislation mandates monitoring AI applications within state agencies.
  • Public-private partnerships: Collaborations between state governments and tech companies are fostering the development of AI governance frameworks.

AI Capacity Building

  • Educational initiatives: There’s a growing emphasis on integrating AI and computer science education in schools, with over 200 CEOs advocating for mandatory AI courses.
  • Workforce development: States are investing in training programs for public sector employees to enhance AI literacy and skills.
  • AI innovation and learning hubs: Many states are setting up AI innovation and learning hubs within and between agencies. These hubs will increasingly be responsible for training staff as they experiment and test new AI technologies and use cases for government.

Technical Infrastructure & Capabilities

  • Sandbox and testing environments: Many state governments are establishing infrastructure for testing and vetting AI models in contained environments.
  • LLM vendor adoption: New products like ChatGPT Gov are designed for secure government use.
  • Cybersecurity focus: With the rise of AI applications, there is a heightened emphasis on securing technical infrastructure against potential threats.
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Partner with us

Let’s build your state’s AI readiness together

We’ve partnered with states across the country to develop integrated benefits applications, document uploaders, and other improvements to make the benefits delivery process easier for both clients and state agencies.

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Methodology

To develop a comprehensive view of state-level AI readiness and use, we conducted extensive desk research by reviewing publicly available materials. This included:

  • Executive orders: Gubernatorial executive actions that established task forces, governance frameworks, or AI strategies.
  • Legislation and policies: Laws and bills related to artificial intelligence.
  • Agency guidance and reports: Strategic plans, policy documents, and technical guidance issued by state agencies, particularly IT departments.
  • Media and trade articles: Local and national news coverage, civic tech blogs, and industry reporting.
  • Direct state input: Opportunity for direct feedback and correction from states upon reviewing draft analysis.

Acknowledgements

The Government AI Landscape Assessment was made possible by the work of many people. We are especially grateful to Kyle Doherty for his data visualization design support, and to Stephen Rockwell for leading our research and analysis efforts.

The Assessment was supported by Code for America’s generous partners and funders, including Google.org and JPMorganChase. The findings and conclusions contained within the Government AI Landscape Assessment are those of the authors and do not necessarily reflect positions or policies of the funders.