Getting Started

Getting Started with AI Product Management

Your step-by-step guide to understanding AI product fundamentals and implementing them in your product strategy.

Key Steps to AI Product Success

Follow these steps to effectively integrate AI into your product strategy.

1

Understand AI Types

Know the different AI product types and their appropriate use cases.

Key Activities:

  • Learn the differences between AI Tools, Copilots, Workflows, Agents, and Infrastructure
  • Identify which AI types are relevant to your product needs
  • Understand the key capabilities and limitations of each AI type
2

Identify AI-Appropriate Problems

Not every problem needs AI. Learn to identify where AI adds value.

Key Activities:

  • Evaluate problems based on pattern recognition, prediction needs, or data scale
  • Assess if traditional software solutions would be more appropriate
  • Consider the AI ROI compared to conventional approaches
3

Assess Data Requirements

Understand what data you need and what you have available.

Key Activities:

  • Inventory existing data sources and evaluate their quality
  • Identify data gaps and develop strategies to fill them
  • Consider privacy, consent, and ethical aspects of data usage
4

Define Success Metrics

Set clear KPIs and success criteria for your AI implementation.

Key Activities:

  • Establish both technical metrics (accuracy, response time) and business metrics (ROI, user adoption)
  • Set realistic performance benchmarks based on your specific use case
  • Plan for continuous measurement and improvement processes

Ready to Go Deeper?

Take the next steps in your AI product journey with these comprehensive resources.

AI Product Canvas

A structured template to plan and design your AI product strategy.

Explore Canvas

Implementation Roadmap

A comprehensive guide to implementing AI from concept to deployment.

View Roadmap

AI PRD Template

A product requirements document template tailored for AI products.

Use Template