Role-Based Programme
RB1537

AI-Powered Delivery Management

Smarter Planning, Execution, Risk Control & Stakeholder Reporting

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Delivery Managers across planning, execution, team coordination, risk management, stakeholder communication, and reporting.
  • Apply AI-assisted techniques to monitor delivery progress, analyse milestones, identify blockers, manage dependencies, and track corrective actions.
  • Use structured prompting for delivery planning, status reviews, risk analysis, escalation, recovery planning, and executive communication.
  • Explore AI-supported approaches for identifying delivery delays, recurring bottlenecks, capacity concerns, and cross-team dependencies.
  • Build responsible AI-assisted delivery workflows while maintaining accountability, governance, data accuracy, and human judgement.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisDelivery Planning AIRisk & Dependency AnalysisPerformance MonitoringMeeting & Reporting AIWorkflow Automation

Who should attend

  • Delivery Managers
  • Project Delivery Managers
  • Program Delivery Managers
  • Service Delivery Managers
  • Project Managers
  • Program Managers
  • Implementation Managers
  • Delivery Leads
  • PMO Professionals
  • Project Controls Professionals
  • Transformation Managers
  • Operations Delivery Managers
  • Client Delivery Managers
  • Delivery Management Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of project, program, or service delivery activities
  • Familiarity with milestones, project plans, risks, issues, dependencies, 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 delivery-management activities
  • Identifying AI applications across planning, execution, coordination, risk management, and reporting
  • Understanding AI assistance versus Delivery Manager and leadership judgement
  • Recognising limitations such as incomplete context, inaccurate assumptions, and unsupported recommendations
Practical activities
  • Mapping a typical Delivery Management workflow
  • Identifying repetitive and information-intensive delivery activities suitable for AI assistance
  • Comparing a traditional delivery-management task with an AI-assisted approach

Scenarios

Delivery Plan to Execution Control

Delivery Objective → AI-Assisted Plan → Milestones → Dependencies → Team Actions → Progress Tracking → Risks & Blockers → Status Review

Participants use AI to organise a sample delivery plan, monitor progress, identify risks and blockers, and prepare a structured delivery-status review.

Delivery Delay to Recovery & Executive Update

Delayed Milestone → AI-Assisted Impact Analysis → Dependencies → Recovery Options → Priority Actions → Escalation → Executive Delivery Report

Participants use AI to analyse a sample delivery delay, identify affected dependencies and recovery options, and prepare a management-ready delivery update.

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