AdvancedProduct Managers

AI Product Strategy for Leaders

For senior PMs, product leaders, and VPs. This path covers writing AI product strategies, making build-vs-buy decisions at scale, pricing AI products, evaluating vendors, and building the data infrastructure that powers AI.

5 modules21 steps~4.5 hours
0% complete0/21 steps
Path Progress: 0% (0/21 steps)
Module 1: Writing Your AI Strategy0/5
Module 2: Build, Buy, and Vendor Decisions0/6
Module 3: Pricing AI Products0/6
Module 4: Measuring AI ROI0/4
Module 5: Scaling AI Across the Organization0/5

After completing this path, you will be able to:

  • Write a complete AI product strategy that connects to business outcomes
  • Make informed build vs. buy and vendor selection decisions
  • Design pricing models for AI-powered products
  • Build a data strategy that supports long-term AI product development

Learning Objectives

  • Write a 7-step AI product strategy document
  • Align AI initiatives with business objectives
  • Find and validate AI product-market fit
📖
How to Write an AI Product Strategy
15m
📖
AI Product-Market Fit
12m
📖
Case Study: ChatGPT's Growth
10m
✏️
25m
🏁
5m

Learning Objectives

  • Evaluate AI vendors using a structured framework
  • Make informed build vs. buy decisions for AI capabilities
  • Assess data strategy requirements for AI initiatives
📖
AI Vendor Evaluation Framework
12m
📖
AI Vendor Comparison Template
8m
🧮
AI Build vs Buy Analyzer
10m
📖
AI Data Strategy
12m
✏️
15m
🏁
5m

Learning Objectives

  • Understand token-based, outcome-based, and usage-based pricing models
  • Calculate unit economics for AI features
  • Model different pricing scenarios
📖
AI Pricing Models
12m
📖
Token Cost per Interaction
5m
🧮
AI SaaS Pricing Game
10m
🧮
LLM Cost Estimator
8m
✏️
15m
🏁
5m

Learning Objectives

  • Build an ROI model for AI initiatives
  • Measure and communicate AI feature ROI
  • Present AI investments to executives
📖
How to Measure ROI on AI Features
10m
🧮
AI Feature ROI Calculator
10m
📖
AI Cost per Output
5m
✏️
15m

Learning Objectives

  • Scale AI product development beyond a single team
  • Learn from case studies of successful AI organizations
  • Build repeatable processes for AI product launches
📖
Case Study: GitHub Copilot
10m
📖
Case Study: Notion AI
10m
📖
AI Tools Across the SDLC
10m
✏️
15m
🏁
5m