AI Product Management

AI Product Management is written for product managers, founders, designers, engineers, analysts, consultants, and leaders who need a disciplined way to turn promising AI ideas into accountable products. The book begins with a simple question: does the problem deserve an AI solution, and can the team prove that users, data, model behavior, economics, review, and risk are ready? Across twelve chapters, readers learn how to frame bounded use cases, compare non-AI alternatives, define requirements, assess tools, design human review, test normal and failure cases, and set release gates that support pause, correction, rollback, or retirement. Concrete frameworks, scorecards, workflow records, risk registers, readiness checks, and a running public-service case connect strategic choices with daily operating decisions. Particular attention is given to source authority, permissions, traceability, abstention, accessibility, security, privacy, cost, incident response, vendor change, and the people affected after launch. The aim is clear judgment under uncertainty, supported by evidence another professional can inspect. It treats speed as an advantage only when responsibility remains visible throughout work. Readers finish with a thirty-day action plan and a complete work pack for assessing opportunities, planning pilots, measuring outcomes, managing controls, and deciding when to adopt, restrict, redesign, or stop an AI product.