State Government AI Landscape Analysis Part 2: Taking Stock - How Ready Are States for AI?

Code for America's State Government AI Landscape Assessment reveals that state governments are deeply interested in artificial intelligence—but vary widely in how prepared they are to use it. This assessment is the first of its kind to systematically evaluate AI readiness across all 50 states. We analyzed leadership structures and support, staff skills and training development, and infrastructure capacity to understand where governments stand and where they need to go. As AI becomes increasingly central to how services are delivered, this baseline provides vital insight into which states are positioned to lead and which need greater investment to ensure equitable and effective adoption.

My first encouragement is to go directly to the report and check out the interactive map which provides details for each state. 

Across the three readiness dimensions we evaluated—Leadership & Governance, AI Capacity Building, and Technical Infrastructure & Capabilities—we found that:

• Leadership & Governance: Most states fall in the developing stage, with task forces or AI advisory groups in place but lacking formal authority or a Chief AI Officer. A few have established structures, but very few have statutory, cross-agency integration or accountability mechanisms.
• AI Capacity Building: This is the area where states most commonly lag. Most are in the early or developing stages, with limited technical resources, modest workforce training efforts, and inconsistent data infrastructure. A handful of states have structured training, cloud-based infrastructure, and teams focused on AI service delivery.
• Technical Infrastructure & Capabilities: Similar to capacity building, many states remain in early and developing stages. Infrastructure challenges such as outdated systems, lack of scalable platforms, and limited cross-agency data capabilities slow AI implementation. States further along have invested in modernization, interoperability, and secure environments for experimentation.

To illustrate how states performed overall across the readiness framework, we developed a visual readiness breakdown. The bar chart below reflects the distribution of states across each of the four readiness levels—Early, Developing, Established, and Advanced—within each of the three dimensions.

Readiness Levels by Dimension (Official Assessment Data):

These figures are illustrative and reflect the broad trends we observed across the nation. Most states sit in the "developing" tier, with early policies, pilots, and governance discussions underway—but relatively few have progressed to the established or advanced levels in any dimension.

• Most states are in the developing stage. They have early AI strategies, executive orders, or pilot projects, but lack full implementation or statewide coordination.
• A few states have reached the established stage, with dedicated AI offices or officers, training programs, and ethical frameworks in place.
• Very few states could be considered advanced, with integrated AI governance, sustained funding, and have moved beyond readiness to large-scale experiments and implementations.

One clear trend: leadership and interest are outpacing readiness. Governors and legislators are creating task forces and issuing executive orders, but the policy, staffing, and technical groundwork often lags behind.

States face common barriers: workforce skills gaps, limited budgets, outdated infrastructure, and uncertainty about ethical or regulatory implications. But they also have significant opportunities: AI can help improve service delivery, detect fraud, and personalize support for residents.

This moment is critical. States that invest now in building capacity and creating thoughtful policies will be positioned to lead with integrity and impact. Others risk falling behind or implementing AI in ways that are ineffective or inequitable.

My hope is that this assessment provides a roadmap to accelerate responsible readiness.