Democratic and Public AI: Practical Strategies for Buying, Building, and Governing AI

Launching October 2026.

As artificial intelligence becomes embedded in public services and government operations, governments face a defining question: how much control will the public retain over the technologies we use?

The choices public institutions make today about procurement, infrastructure, and governance will shape whether AI systems serving the public are governed and designed in ways that advance public values and democratic accountability and solve problems.

This three-part series explores how governments are acquiring AI today, what those choices mean for innovation, cost, flexibility, transparency, and public oversight, and what alternatives are emerging. Participants will examine the ideas behind public and democratic AI, explore why the distinction matters, and learn from practical examples of governments building, buying and governing AI in ways that preserve public control while fostering innovation and effective problem solving.

Drawing on real-world case studies and conversations with practitioners, researchers, and policymakers, the series provides practical strategies for procuring, designing, governing, and implementing AI systems in government agencies in the public interest.

Learning Goals

• Understand how current AI procurement and deployment choices affect public control, flexibility, and long-term capacity.

• Understand the arguments for and against commercial, sovereign, public and democratic AI.

• Evaluate practical strategies for avoiding vendor lock-in and increasing transparency, interoperability, and accountability.

• Identify opportunities to apply public and democratic AI principles to how you build, buy and manage technology.