In today’s AI-driven landscape, product teams are under pressure to move faster, from idea to validated opportunity, while reducing risk and increasing customer impact. Traditional discovery methods alone are no longer enough.

AI for Product Discovery and Strategy equips product leaders, product managers, and teams with practical ways to integrate AI into discovery, strategy, and decision-making. Learn how to accelerate insight generation, test assumptions more effectively, and move from intuition-driven decisions to evidence-based product strategy.

This hands-on microcredential course blends modern product discovery techniques with AI-powered tools to help you uncover customer needs, validate opportunities, and prioritize investments with greater confidence.

Reach out to training@lithespeed.com to learn about our Group, Veteran, Military, Government/GSA, Unemployment and Student discounts.

Upcoming Classes

What you'll learn

By the end of this course, participants will be able to:

  • Apply AI to accelerate product discovery and insight generation
  • Use AI tools to analyze customer feedback, market trends, and user behavior
  • Frame better product hypotheses using Jobs-to-Be-Done and outcome thinking
  • Rapidly define and validate MVPs and Minimum Marketable Products (MMPs)
  • Improve prioritization using data-driven and AI-augmented insights
  • Identify high-value opportunities aligned to business and customer outcomes
  • Balance human judgment with AI-driven recommendations
  • Build a repeatable, scalable discovery process powered by AI
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Who Should Attend?

This course is ideal for:

  • Product Managers & Product Owners looking to improve discovery and strategy
  • Business Leaders & Executives responsible for product direction and investment decisions
  • Innovation & Strategy Teams driving new product or capability development
  • Agile Coaches & Consultants supporting product-centric transformations
  • Project Managers transitioning to product roles

No technical or AI background is required, this course focuses on practical application, not coding.

SAMPLE AGENDA

Foundations of Modern Product Discovery

  • From project mindset to product operating model
  • Outcome-driven thinking and hypothesis framing
  • Common discovery challenges in today’s environment

AI in Product Discovery

  • Where AI fits in the discovery lifecycle
  • Overview of practical AI tools for product teams
  • Using AI to synthesize research and uncover insights

Customer & Market Insights

  • Jobs-to-Be-Done and customer journey mapping
  • AI-assisted analysis of qualitative and quantitative data
  • Identifying unmet needs and opportunity spaces

Opportunity Framing & Prioritization

  • Defining MVPs and MMPs with AI support
  • Prioritization techniques using AI-driven insights
  • Linking discovery to business outcomes and value

Experimentation & Validation

  • Designing fast, effective experiments
  • Using AI to simulate, test, and refine hypotheses
  • Measuring success and learning quickly

Scaling Discovery with AI

  • Building repeatable discovery practices
  • Embedding AI into product workflows
  • Governance, ethics, and responsible AI use

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