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Course

Enterprise AI Product Management for Building AI Products

A product-management-led course for making credible, responsible, and evidence-based decisions about enterprise AI products and features.

The workplace problem

Why this learning matters

Product leaders are expected to identify, define, launch, and scale AI-enabled products without a reliable way to distinguish useful opportunities from hype, set evaluation gates, or connect product judgment with technical and governance constraints.

Intended outcomes

What participants will learn to do

  • Identify AI product opportunities that connect a real user or enterprise need with credible AI capability.
  • Define product requirements, evaluation expectations, and decision gates for an AI-enabled product or feature.
  • Coordinate product choices with engineering, data, security, legal, risk, and operating stakeholders while retaining accountable product judgment.
  • Frame adoption, trust, operational learning, and value evidence needed after launch.

Application at work

How participants can apply it at work

  • An AI product opportunity brief with assumptions, constraints, and decision criteria.
  • A product requirements and evaluation-gate artifact for a representative AI-enabled product or feature.
  • A launch-and-learning evidence plan covering value, adoption, trust, and operating review.

Shaped to context

Shaped around your context

Flow Cracker shapes the workshop or cohort pathway around the customer's product context, approved tools, governance constraints, representative opportunities, operating rhythm, and any specialist review the work requires.

Entry context: Participants should bring practical product-lifecycle experience; specialist AI engineering knowledge is not required.

Who it is for

Who this is for

  • Enterprise product managers and product owners
  • Senior product leads and product strategy leaders
  • Business-technology leaders responsible for AI-enabled products

Opportunity lenses

  • AI in the product

Capabilities strengthened

  • Product Discovery & Decision Practice
  • Engineering, Architecture & Verification
  • Enterprise, Portfolio & Investment Flow

Connected learning

Discuss the context

Shape the learning around the work that needs to change

Share the audience, workplace problem, constraints, and evidence you want the learning to address.

Discuss this learning need