Role-Based Programme
RB1213

AI for Product Ownership

Smarter Backlog Management, User Stories & Agile Delivery Decisions

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Product Owners across backlog management, requirement clarification, prioritisation, sprint preparation, and stakeholder communication.
  • Apply AI to analyse user needs, refine backlog items, draft user stories, and improve acceptance criteria.
  • Use AI to support prioritisation, dependency analysis, release preparation, and Agile decision-making.
  • Develop practical skills for backlog refinement, sprint-readiness reviews, stakeholder alignment, and product-delivery reporting.
  • Understand responsible AI use, confidentiality, data accuracy, bias, intellectual property, and human oversight in Product Ownership.

Tools covered

Generative AI AssistantsAI Search & ResearchBacklog AnalysisUser Story DevelopmentAcceptance Criteria SupportRequirement ClarificationPrioritisation SupportSprint Planning AssistanceStakeholder CommunicationAgile Reporting

Who should attend

  • Product Owners
  • Senior Product Owners
  • Associate Product Owners
  • Agile Product Owners
  • Digital Product Owners
  • Platform Product Owners
  • Application Product Owners
  • Product Managers
  • Business Analysts
  • Scrum Team Members
  • Agile Delivery Professionals
  • Product Operations Professionals
  • Project Managers Working with Agile Teams
  • Product / Service Management Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of Agile, Scrum, product delivery, or business requirements
  • Familiarity with product backlogs, user stories, sprints, or stakeholder requirements is helpful
  • Basic analytical, communication, and digital-tool skills
  • No programming or technical AI knowledge required
  • Prior AI-tool experience is helpful but not mandatory

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to Product Ownership
  • Exploring AI support across backlog management, requirements, prioritisation, and sprint preparation
  • Distinguishing AI assistance from Agile management, issue-tracking, and workflow platforms
  • Understanding AI limitations, hallucinations, bias, and delivery-related risks
Practical activities
  • Identifying recurring Product Owner activities suitable for AI assistance
  • Comparing traditional and AI-assisted Product Ownership workflows
  • Mapping AI opportunities across the backlog-to-delivery lifecycle

Scenarios

Stakeholder Request to Sprint-Ready Backlog Item

Stakeholder Request → Problem Clarification → User Need → User Story → Acceptance Criteria → Dependency Review → Prioritisation → Sprint Readiness

Participants use AI to convert a sample stakeholder request into a refined, prioritised, and sprint-ready backlog item while validating assumptions and dependencies.

Backlog Overload to Prioritised Delivery Plan

Backlog Items → Duplication & Gap Review → Business Value → Customer Impact → Dependencies → Priority Ranking → Sprint Candidates → Stakeholder Summary

Participants use AI to analyse a sample overloaded backlog, identify overlaps and dependencies, support prioritisation, and prepare a clear delivery recommendation for stakeholder discussion.

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