Role-Based Programme
RB1214

AI for Product Ownership

Backlog Intelligence, Agile Prioritisation & Value Delivery

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Develop practical AI capabilities for backlog management, requirements clarification, user stories, prioritisation, and agile product delivery.
  • Apply AI to analyse customer needs, stakeholder inputs, feature requests, business priorities, dependencies, and delivery risks.
  • Use AI to strengthen backlog refinement, acceptance criteria, sprint preparation, release planning, and stakeholder communication.
  • Improve Product Owner decision-making through structured prioritisation, evidence synthesis, product analytics, and value-based planning.
  • Apply responsible AI practices related to customer data, confidentiality, bias, requirement accuracy, intellectual property, and human ownership of product decisions.

Tools covered

Generative AI AssistantsAI Search & ResearchRequirement AnalysisBacklog AnalysisUser Story DevelopmentAcceptance Criteria SupportPrioritisation SupportSprint Planning SupportStakeholder AnalysisProduct AnalyticsRelease PlanningExecutive Summarisation

Who should attend

  • Product Owners
  • Senior Product Owners
  • Associate Product Owners
  • Digital Product Owners
  • Technical Product Owners
  • Platform Product Owners
  • Service Product Owners
  • Product Managers
  • Business Analysts
  • Agile Business Analysts
  • Scrum Team Members
  • Product Operations Professionals
  • Delivery Managers
  • Agile Project Professionals
  • Product & Service Management Professionals

Prerequisites & Participant Readiness

  • Experience in product ownership, product management, business analysis, agile delivery, or service management
  • Familiarity with product backlogs, user stories, sprint planning, and stakeholder requirements
  • Basic familiarity with Generative AI tools is recommended
  • Understanding of agile or iterative delivery concepts
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, multimodal AI, and AI assistants
  • Exploring AI applications across requirements, backlogs, sprint preparation, and release planning
  • Understanding how AI differs from agile, product, and work-management platforms
  • Recognising hallucinations, unsupported assumptions, and incomplete requirements
Practical activities
  • Mapping Product Owner responsibilities to practical AI applications
  • Identifying high-value versus low-value AI use cases
  • Comparing traditional and AI-assisted Product Ownership workflows

Scenarios

Customer Requirement to Sprint-Ready Backlog

Customer Feedback → Requirement Analysis → User Stories → Acceptance Criteria → Dependency Review → Prioritisation → Backlog Refinement → Sprint Readiness

Participants use AI to analyse a simulated customer requirement, create structured user stories and acceptance criteria, identify dependencies, and prepare a prioritised sprint-ready backlog.

Backlog Overload to Value-Based Release Plan

Backlog Review → Business Value → Customer Impact → Effort & Risk → Stakeholder Priorities → Dependency Mapping → Release Scenarios → Product Decision

Participants use AI to analyse an overloaded product backlog, evaluate competing priorities, identify trade-offs, and develop a structured value-based release recommendation.

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