Role-Based Programme
RB1550

AI-Powered Agile Project Management

Smarter Sprint Planning, Delivery Control & Stakeholder Alignment

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

Programme Objectives

  • Apply AI across Agile Project Management activities including planning, backlog coordination, sprint execution, risk management, stakeholder communication, and delivery reporting.
  • Use AI-assisted techniques to analyse sprint data, delivery trends, dependencies, risks, issues, capacity, and project progress more efficiently.
  • Develop structured workflows for Agile planning, iteration tracking, change coordination, impediment management, escalation, and governance.
  • Improve delivery visibility through AI-assisted dashboards, forecasting, sprint analytics, dependency tracking, and management reporting.
  • Apply responsible AI practices covering project-data accuracy, team confidentiality, bias, forecast uncertainty, governance, and human oversight.

Tools covered

Generative AI AssistantsAgile Planning SupportBacklog AnalysisSprint AnalyticsProject TrackingRisk & Dependency AnalysisStakeholder CommunicationSpreadsheet AnalysisAgile ReportingWorkflow Automation

Who should attend

  • Agile Project Managers
  • Project Managers
  • Delivery Managers
  • Agile Delivery Managers
  • Program Managers
  • Scrum Masters
  • Iteration Managers
  • PMO Professionals
  • Transformation Managers
  • Implementation Managers
  • Project Analysts
  • Agile Team Leads
  • Workstream Leads
  • Project & Program Management Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of Agile, Scrum, project management, or delivery-management activities
  • Familiarity with backlogs, sprints, milestones, risks, dependencies, and status reporting is helpful
  • Basic spreadsheet and project-tracking skills
  • Basic awareness of Generative AI is helpful
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, analytics, and automation in Agile project delivery
  • Identifying AI applications across planning, sprint tracking, risk management, reporting, and stakeholder communication
  • Understanding AI assistance versus Agile Project Manager accountability and decision-making
  • Recognising risks related to inaccurate project data, weak assumptions, confidentiality, and over-automation
Practical activities
  • Mapping the Agile delivery lifecycle to AI-assisted activities
  • Identifying repetitive project-management tasks suitable for AI support
  • Comparing traditional and AI-assisted Agile project workflows

Scenarios

Agile Project Initiation to Release Recovery Plan

Business Objective → AI-Assisted Roadmap → Backlog Planning → Sprint Delivery → Dependency Tracking → Delay Detection → Recovery Options → Release Forecast → Stakeholder Update

Participants manage a simulated Agile project from initiation through multiple sprints, identify emerging delivery and dependency risks, and develop a structured recovery and communication plan.

Multi-Sprint Delivery Data to Executive Governance Report

Sprint Metrics + Milestones + Risks + Dependencies + Change Requests → AI Analysis → Delivery Health → Forecast Risks → Priority Actions → Executive Dashboard

Participants consolidate Agile project information across multiple iterations, identify delivery trends and governance concerns, and prepare an executive-ready project report with evidence-supported actions and priorities.

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