Role-Based Programme
RB1549

AI-Powered Agile Project Management

Smarter Sprint Planning, Delivery Tracking & Stakeholder Collaboration

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Agile Project Managers across planning, sprint coordination, delivery tracking, risk management, and stakeholder communication.
  • Apply AI-assisted techniques to organise backlog information, monitor sprint progress, identify blockers, and prepare delivery updates.
  • Use structured prompting for sprint planning, dependency analysis, risk reviews, retrospective insights, and management reporting.
  • Explore AI-supported approaches for identifying delivery trends, recurring impediments, schedule concerns, and improvement opportunities.
  • Build responsible AI-assisted Agile workflows while maintaining team ownership, governance, data accuracy, and human judgement.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisAgile Planning AISprint & Backlog AnalysisRisk & Dependency AnalysisMeeting & Reporting AIWorkflow Automation

Who should attend

  • Agile Project Managers
  • Agile Delivery Managers
  • Project Managers
  • Scrum Masters
  • Program Managers
  • Project Coordinators
  • PMO Professionals
  • Agile Coaches
  • Delivery Leads
  • Product Delivery Professionals
  • Project Analysts
  • Iteration Managers
  • Transformation Project Professionals
  • Agile Project Management Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of Agile, Scrum, or project-management concepts
  • Familiarity with sprints, backlogs, milestones, risks, issues, and stakeholder reporting is helpful
  • Basic computer, spreadsheet, and document-handling skills
  • No AI or programming knowledge required
  • No previous AI training required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to Agile project delivery
  • Identifying AI applications across planning, sprint coordination, delivery monitoring, communication, and reporting
  • Understanding AI assistance versus Agile Project Manager and team judgement
  • Recognising limitations such as incomplete context, weak assumptions, and unsupported recommendations
Practical activities
  • Mapping a typical Agile project-management workflow
  • Identifying repetitive and information-intensive Agile activities suitable for AI assistance
  • Comparing a traditional Agile project task with an AI-assisted approach

Scenarios

Agile Project Plan to Sprint Delivery

Project Goal → Backlog → AI-Assisted Sprint Planning → Dependencies → Sprint Execution → Progress Tracking → Risks & Actions

Participants use AI to organise a sample Agile project, support sprint preparation, identify dependencies, and monitor delivery without replacing Product Owner or team decisions.

Multi-Sprint Data to Management Review

Sprint Metrics + Risks + Issues + Dependencies + Team Feedback → AI Analysis → Delivery Trends → Priority Concerns → Improvement Actions → Management Report

Participants use AI to analyse sample Agile project information, identify recurring delivery challenges, and prepare a concise management-ready project review.

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