COURSE :

AI IN PROJECT MANAGEMENT

Overview

Artificial Intelligence is changing how project teams plan, analyse, communicate, monitor and control projects. This
two-day programme equips project managers and project team members with practical methods for applying AI
throughout the project lifecycle.

The programme focuses on real workplace application rather than AI theory. Participants practise using generative AI
and suitable AI-enabled tools to develop project documents, improve scheduling and planning, identify risks, analyse
project information, prepare reports, support decision-making and streamline repetitive project-management activities..

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COURSE OBJECTIVE

  • Apply generative AI appropriately across key stages of the project lifecycle.
  • Develop effective AI prompts for project planning, documentation, analysis and reporting.
  • Use AI to improve project scope definition, work breakdown, scheduling and resource planning.
  • Analyse project risks, issues and project information with AI assistance.
  • Improve selected project communication, monitoring and reporting activities through AI and automation.
  • Develop a practical AI adoption plan while recognising data-security, accuracy, governance and human-oversight
    requirements.

LEARNING OUTCOMES

Upon completion, participants would be able to:

After completing the programme, participants should be capable of using AI as a practical project-management
productivity and decision-support tool across project initiation, planning, scheduling, risk management, stakeholder
communication, monitoring and reporting, while applying appropriate human judgement, verification and governance.

COURSE OUTLINE

Module 1: AI and the Future of Project Management
• AI, Generative AI and automation in project environments
• Where AI adds value across the project lifecycle
• AI as a project-management assistant versus human decision-making
• Common AI use cases for project teams
• Limitations, hallucinations, confidentiality and responsible AI use
• Identifying repetitive and time-consuming PM activities

Module 2: Prompt Engineering for Project Professionals
• Principles of effective prompting
• Providing project context, role, objective and constraints
• Creating structured outputs and reusable templates
• Iterative prompting and improving AI responses
• Using AI to analyse rather than simply generate information
• Verifying AI-generated project information

Module 3: AI for Project Initiation and Scope Management
• Developing and refining project objectives
• Drafting project charters
• Identifying requirements and assumptions
• Developing scope statements, deliverables and acceptance criteria
• Detecting potential scope gaps and ambiguities

Module 4: AI for Work Breakdown Structure and Project Planning
• Converting scope into project deliverables
• Developing a Work Breakdown Structure (WBS)
• Breaking deliverables into manageable work packages
• Identifying activities and dependencies
• Reviewing project plans for missing activities

Module 5: AI-Assisted Scheduling and Resource Planning
• Translating activities into a project schedule
• Activity sequencing and dependencies
• Identifying potential schedule conflicts
• Resource requirements and allocation
• Analysing schedule scenarios
• Using AI alongside conventional scheduling tools

Module 6: AI for Project Risk and Issue Management
• AI-assisted risk identification
• Developing risk statements
• Probability and impact considerations
• Risk categorisation and prioritisation
• Developing mitigation and contingency actions
• Differentiating risks, issues and assumptions

Module 7: AI for Stakeholder Management, Meetings & Communication
• Stakeholder identification and analysis
• Tailoring communication for different stakeholders
• Drafting professional project correspondence
• Meeting agenda preparation and meeting summarisation
• Extracting decisions and action items
• Escalation communication using AI

Module 8: AI for Project Monitoring, Analysis & Decision Support
• Analysing project progress information
• Comparing planned versus actual performance
• Identifying delays, bottlenecks and emerging issues
• Analysing action registers and project data
• Supporting root-cause investigation
• Scenario analysis and decision support

Module 9: AI-Powered Project Reporting & Workflow Automation
• Creating weekly and monthly project reports
• Executive project summaries
• Converting raw project information into management reports
• Automating repetitive documentation workflows
• AI-assisted dashboards and reporting concepts
• Integration opportunities with spreadsheets, PM platforms and automation tools

Module 10: Practical AI Project Management Challenge & Workplace Action
Plan
• Apply AI to project objectives and scope
• WBS and activity planning
• Schedule considerations and risk identification
• Stakeholder communication and status analysis
• Management reporting and automation opportunities
• Prepare a 30-day AI in Project Management Action Plan