This capstone unit synthesizes proactive AI product management, cross-functional collaboration, responsible AI foundations, and practical ideation techniques. Learners will apply frameworks to anticipate user needs, generate and prioritize AI/ML use cases, coordinate with partner roles, and assess ethical and feasibility tradeoffs to prepare an actionable next-stage product plan.
Learning Objectives
- analyze user behaviors, market signals, and product telemetry to identify and prioritize emergent user needs that can be addressed with AI features
- apply practical ideation techniques to generate, document, and prioritize AI/ML use cases using defined impact, feasibility, privacy, and business criteria
- demonstrate effective cross-functional collaboration by mapping role responsibilities, communication flows, and handoffs between product, engineering, design, data science, legal/compliance, and operations for an AI product lifecycle
- evaluate ethical, legal, and technical feasibility considerations for proposed AI features and propose concrete mitigation and monitoring plans (e.g., bias audits, data governance, fallback strategies) for deployment readiness
Curriculum
- 1 Section
- 6 Lessons
- 30 hours
Expand all sectionsCollapse all sections
- Unit 4 — AI-First Product Strategy & Ethics6
- 1.1Proactive Product Management—Anticipating User Needs with AI20 mins
- 1.2How the AI-Experiences PM Interacts with Other Roles20 mins
- 1.3Responsible AI Foundations—Ethical and Feasibility Considerations20 mins
- 1.4and Key Takeaways20 mins
- 1.5Practical Ideation Techniques for AI/ML Use Cases—Thinking Like an AI-First Product Manager20 mins
- 1.6and Key Takeaways20 mins
Instructor
Free
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