Role-Based Programme
RB1536

AI-Powered Delivery Management

Smarter Planning, Execution, Risk Control & Stakeholder Delivery

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Duration
4 Hours
Level
Awareness
Delivery
Instructor-Led
Format
Awareness Session

Programme Objectives

  • Understand how AI can support Delivery Managers across planning, execution tracking, risk management, stakeholder communication, and reporting.
  • Explore practical prompting techniques for delivery plans, status reviews, risk summaries, escalation notes, and management updates.
  • Apply AI to organise delivery information, identify blockers, structure actions, and prepare management-ready outputs.
  • Identify opportunities to improve delivery visibility, coordination, follow-up discipline, and decision support.
  • Recognise confidentiality, data accuracy, governance requirements, commitments, and human-review responsibilities when using AI.

Tools covered

Generative AI AssistantsAI-Assisted Delivery PlanningRisk & Issue TrackingMeeting SummarisationDelivery Status ReportingStakeholder CommunicationDependency ManagementBasic Workflow Automation

Who should attend

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

Prerequisites & Participant Readiness

  • Basic understanding of project, program, or delivery-management activities
  • Familiarity with plans, milestones, risks, issues, stakeholders, or delivery reporting is helpful
  • Basic computer and office-productivity skills
  • No AI or programming knowledge required
  • No previous Generative AI experience required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to Delivery Management
  • Identifying AI applications across planning, execution monitoring, risk management, and reporting
  • Understanding AI assistance versus Delivery Manager judgement and accountability
  • Recognising activities where validated project information and human oversight remain essential
Practical activities
  • Mapping common Delivery Manager activities to potential AI applications
  • Comparing a traditional delivery-management task with an AI-assisted approach

Scenarios

Delivery Plan to Execution Control

Delivery Brief → AI-Assisted Plan → Milestones → Dependencies → Risks → Owners → Execution Tracker

Participants use AI to convert a sample delivery brief into a structured execution plan and tracker covering milestones, dependencies, risks, ownership, and follow-up actions.

Delivery Challenges to Management Escalation

Progress Updates + Delays + Risks + Stakeholder Inputs → AI Consolidation → Root Issues → Recovery Actions → Escalation Summary

Participants use AI to consolidate sample delivery challenges, identify priority issues, structure recovery actions, and prepare a concise management escalation while retaining final delivery decisions with authorised leaders.

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