From AI Idea to Measurable Product: A Product Leader’s Playbook for Building AI That Actually Delivers

About this session

Most AI products do not fail because of the model they fail because teams choose the wrong problem, cannot define quality, underestimate operational cost, or never build a path from prototype to adoption. Drawing on 23+ years leading enterprise product and digital-transformation initiatives and insights from my book, AI Product Management, I will share a practical framework for moving from an AI opportunity to a measurable, trustworthy product. Attendees will learn how to select use cases, define success metrics beyond model accuracy, manage human-in-the-loop and governance decisions, account for cost and risk, and turn early experiments into sustainable business value. The session will include candid lessons on what breaks, what to measure, and what actually moves outcomes.

Speaker

• Nilesh Dhage, Director Product Management, Financial Services

Key takeaways

• An AI use-case prioritization scorecard: customer value, feasibility, data readiness, risk, and cost.
• An outcome-based metric stack: business impact, user trust, product adoption, model quality, and operational cost.
• A prototype-to-production readiness checklist.

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