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AI Product Strategy

via Nielsen Norman Group

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Learn facilitation tools that help you move conversations from hype to evidence and guide your organization toward responsible, effective AI adoption. As teams rush to add AI into their products, many features still launch for novelty rather than real impact.

Syllabus

What you will learn

Identify high-value AI opportunities

Distinguish between hype-driven and value-driven AI features
Use a Jobs-to-be-Done framework to pinpoint where AI uniquely delivers value
Identify friction points that AI can meaningfully reduce or resolve

Facilitate evidence-based AI strategy conversations

Facilitate cross-functional discussions that align teams on AI priorities
Guide stakeholders toward balanced, evidence-driven thinking, whether they’re risk-averse or overly optimistic
Lead productive conversations when teams disagree on AI direction, value, or risk tolerance
Shift teams from AI-first or AI-avoidant reactions to a value-first, problem-first approach
Use workshop formats and facilitation tools to build alignment and shared ownership

Evaluate and prioritize AI features

Apply a prioritization framework to score and rank AI ideas
Define evaluation criteria to ensure AI features align with organizational goals
Use hands-on diagnostic scorecards with real-world case studies
Prioritize a roadmap of AI features based on potential user and business impact

Plan for adoption, trust and long-term value

Establish design criteria that set accurate expectations and communicate system confidence
Analyze trust loops and behavioral adoption dynamics
Connect UX metrics to growth and business metrics to demonstrate AI feature ROI
Explore how real companies scale AI capabilities over time