Role-Based Programme
RB1538

AI-Powered Delivery Management

Smarter Execution, Risk Control & Delivery Performance

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

Programme Objectives

  • Apply AI across Delivery Management activities including planning, execution tracking, risk management, resource coordination, stakeholder communication, and reporting.
  • Use AI-assisted techniques to analyse milestones, dependencies, delivery risks, resource constraints, issues, and performance trends more efficiently.
  • Develop structured workflows for delivery planning, cross-functional coordination, escalation, change management, recovery planning, and governance.
  • Improve delivery visibility through AI-assisted dashboards, exception analysis, forecast support, action tracking, and management reporting.
  • Apply responsible AI practices covering data accuracy, confidentiality, forecast uncertainty, decision accountability, and human oversight.

Tools covered

Generative AI AssistantsDelivery Planning SupportProject & Program AnalyticsSchedule AnalysisResource & Capacity AnalysisRisk & Issue ManagementStakeholder CommunicationSpreadsheet AnalysisDelivery ReportingWorkflow Automation

Who should attend

  • Delivery Managers
  • Senior Delivery Managers
  • Program Managers
  • Project Managers
  • Service Delivery Managers
  • Implementation Managers
  • Agile Delivery Managers
  • Transformation Managers
  • PMO Managers
  • Workstream Leads
  • Operations Delivery Leaders
  • Project Controls Professionals
  • Client Delivery Professionals
  • Project & Program Management Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of project, program, service, or implementation delivery activities
  • Familiarity with project plans, schedules, resources, risks, issues, stakeholders, 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, automation, and their role in delivery management
  • Identifying AI applications across planning, coordination, risk, resources, communication, and reporting
  • Understanding AI assistance versus Delivery Manager accountability and decision-making
  • Recognising risks related to poor-quality data, unrealistic recommendations, confidentiality, and over-automation
Practical activities
  • Mapping the delivery lifecycle to AI-assisted opportunities
  • Identifying repetitive coordination and reporting tasks suitable for AI support
  • Comparing traditional and AI-assisted delivery-management workflows

Scenarios

Delivery Slippage to Recovery Plan

Delivery Plan → AI-Assisted Schedule & Dependency Review → Delay Detection → Risk & Resource Analysis → Recovery Options → Action Plan → Stakeholder Update

Participants analyse a simulated delivery that has fallen behind schedule, identify the main constraints and dependencies, develop recovery options, and prepare a structured management and stakeholder communication plan.

Multi-Workstream Delivery to Executive Governance Report

Milestones + Resources + Risks + Issues + Dependencies + Changes → AI Analysis → Delivery Health → Priority Exceptions → Forecast Risks → Executive Report

Participants consolidate multiple workstream updates, identify emerging delivery risks and bottlenecks, and prepare an executive-ready governance report with clear actions, ownership, and priorities.

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