appendix-a

Appendix A. AI development toolbox

 

This appendix provides actionable tools, structured summaries, and practical checklists to help you apply the concepts introduced in chapters 2–12. Whether you are learning AI product management for the first time or looking for a quick reference, this section serves as a study aid and a cheat sheet to reinforce key frameworks, methodologies, and decision-making processes.

Use it to internalize essential knowledge, accelerate implementation, and streamline AI-driven product decisions in your daily work.

A.1 Chapter 2 (Discovering and prioritizing AI opportunities)

A.1.1 Sourcing AI ideas and opportunities

Blueprint: AI opportunity tree

Use the four key AI benefits to structure your opportunity exploration:

AI benefit
Example Use Cases
Automation and productivity
AI-powered chatbots, invoice processing, fraud detection
Improvement and augmentation
AI-assisted writing tools, AI-powered design assistance
Personalization
Tailored content recommendations, AI-driven UX customization
Innovation and inspiration
AI-generated design concepts, AI-assisted scientific discovery

Checklist: Sourcing AI ideas

  • Analyze customer feedback (support tickets, surveys, product reviews)
  • Use team insights (internal brainstorming, domain expertise)
  • Monitor competitors (benchmarking AI-driven features)
  • Track technological advancements (LLMs, computer vision, new AI frameworks)
  • Consider market forces (regulatory changes, AI-driven shifts in industry trends)

A.1.2 Identifying AI-friendly problems

A.1.3 Balancing quick wins vs. long-term AI investments

A.2 Chapter 3 (Mapping the AI solution space)

A.2.1 Identifying data modalities

A.2.2 Choosing between supervised and unsupervised learning

A.2.3 Choosing the right AI approach

A.2.4 Choosing an AI interface

A.3 Chapter 4 (Predictive AI)

A.3.1 Overview of common analytical algorithms