AI for Product Owners

From Task Management to Hypothesis Management

The role of the Product Owner is shifting. As AI tools take on more of the administrative work of backlog management, the PO's value moves toward structuring work as testable hypotheses — defining outcomes, not just outputs. This course prepares you for that shift by teaching you to use AI not just to write better user stories, but to think differently about what belongs in a backlog and why.

What You'll Learn

Upon successful completion, you will be able to:

• Identify which product owner responsibilities are suitable for AI augmentation and which require irreplaceable human skills
• Recognize primary risks — ethical, data privacy, and algorithmic bias — when using AI tools with team and product information
• Apply prompt engineering principles to generate tangible outputs that support scrum events, artifacts, and commitments
• Use AI to assist in generating and refining user stories and product backlog items — ensuring clarity, conciseness, and alignment with business value
• Utilize AI tools to order a product backlog based on customer needs, strategic goals, and other parameters

Who This Course Is For

• Product Owners and Product Managers seeking to integrate AI into backlog management
• Business Analysts involved in requirements definition and prioritization
• Agile team members supporting product planning and stakeholder communication
• Anyone responsible for product decision-making in an Agile environment

No prior AI experience is required. The course is applicable across industries — not limited to software products.

What This Course Does Not Cover

This is a foundation-level microcredential. It does not cover:

• AI product strategy at the organizational level
• Agent-based product systems
• Retrieval-Augmented Generation (RAG) for product knowledge bases
• AI governance and enterprise deployment

For advanced AI capability in product leadership, see our Advanced Layer programs.