A book built alongside public research.

AI for Government is a practical field guide for public-sector leaders who need to move AI from policy statements and pilot projects into real operating practice. It bridges the gap between paper governance and operating governance.

Government agencies are under pressure to deliver better services at lower cost while navigating tight budgets, small teams, legacy systems, workforce anxiety, legislative scrutiny, and public accountability. AI promises help, but adoption fails when leaders treat governance as a document, experimentation as strategy, or launch as the finish line.

This book shows how to build AI capability that lasts. It guides leaders through selecting use cases, evaluating performance, defining value, assessing risk, setting release gates, protecting security and privacy, managing vendors, preparing the workforce, monitoring systems after launch, controlling cost, and responding when systems fail.

Written especially for resource-constrained public-sector organizations, AI for Government offers actionable frameworks, decision tools, and implementation patterns for turning AI ambition into responsible execution. Its central argument is simple: successful AI adoption depends not only on choosing the right technology, but on building the governance, operating discipline, and public trust needed to sustain it.