AI for Project Management Professionals

Course overview

AI for Project Management Professionals is an advanced practical course designed to help project managers, programme managers, PMO professionals, team leaders and project practitioners use Artificial Intelligence, Generative AI, Machine Learning and AI-powered project management tools to improve project planning, estimation, scheduling, risk management, resource allocation, stakeholder engagement, reporting, monitoring and decision-making. The course goes beyond basic AI prompting and focuses on how AI can be integrated into the complete project lifecycle—from business case development and project initiation through planning, execution, monitoring and control, change management, risk management and project closure. It also addresses the emerging role of AI agents, predictive project analytics, intelligent PMOs, responsible AI and human-AI collaboration.

Course objectives

• Understand the role of Artificial Intelligence in modern project management and project delivery.
• Identify practical opportunities for applying AI across the project lifecycle, from initiation to closure.
• Use Generative AI to support project planning, documentation, communication, reporting and decision-making.
• Apply AI to project scheduling, task prioritization, resource allocation and timeline optimization.
• Use AI for cost estimation, budgeting, forecasting and financial monitoring.
• Apply AI-driven risk analytics to identify, assess, prioritize and monitor project risks.
• Use AI for requirements and stakeholder management, including analysis of project requirements and stakeholder communications.

Who should attend

Course content

• MODULE 1: AI and the Changing Project Management Profession Understanding AI in project management What is Artificial Intelligence? Machine Learning Generative AI Large Language Models Predictive AI AI copilots AI agents Automation versus augmentation AI-
• MODULE 2: AI-Powered Project Initiation AI can support project managers before a project is formally launched. Topics Developing project concepts Problem definition Business-case development Project objectives Benefits identification Stakeholder identif
• MODULE 3: AI-Powered Project Planning This is one of the most important modules. Project planning with AI Work Breakdown Structure Activity identification Task decomposition Deliverable definition Milestone development Dependencies Project sequencing AI
• MODULE 4: AI for Project Scheduling and Time Management Scheduling Activity duration estimation Dependency analysis Critical path Milestones Resource constraints Schedule optimization Schedule risk AI applications Detecting unrealistic timelines Identifyi
• MODULE 5: AI for Project Cost Estimation and Budget Management Topics Cost estimation Budget development Cost forecasting Cost variance Budget risks Contingency planning AI applications Historical cost analysis Cost prediction Budget anomaly detection Cos
• MODULE 6: AI for Risk Management This should be a major component of the programme. Risk identification AI can analyse: Project plans Previous projects Contracts Reports Stakeholder information Historical risk registers Risk assessment Probability Imp
• MODULE 7: AI for Resource Management Topics Human resources Skills Equipment Materials Contractors Resource availability Resource utilization AI applications Resource demand forecasting Skills matching Resource allocation Workload balancing Capacity plann
• MODULE 8: AI for Project Performance Monitoring and Control AI-enabled project controls Performance monitoring KPI analysis Progress tracking Variance analysis Trend detection Forecasting AI early-warning systems Identify: Delayed activities Cost overru
• MODULE 9: AI for Project Reporting and Executive Dashboards Traditional reporting Weekly reports Monthly reports Progress reports Status reports Steering committee reports AI-enhanced reporting Automated status reports Executive summaries Variance explana
• MODULE 10: Generative AI for Project Managers This should be a dedicated hands-on module. Executive and PM applications Project documentation Emails Meeting preparation Meeting summaries Action lists Reports Proposals Presentations Project communication
• MODULE 11: AI for Requirements Management Topics Requirements gathering Requirements analysis Requirements documentation User stories Acceptance criteria Requirements traceability AI applications Extracting requirements from documents Detecting ambiguity
• MODULE 12: AI for Stakeholder and Communication Management Stakeholder analysis Stakeholder identification Stakeholder classification Influence analysis Interest analysis Stakeholder risk AI applications Stakeholder mapping Communication planning Personal
• MODULE 13: AI for Meetings and Project Collaboration AI meeting assistants Meeting transcription Meeting summaries Action-item extraction Decision tracking Issue identification Follow-up generation Project knowledge management Project documentation Search
• MODULE 14: AI for Quality Management Quality applications Quality assurance Quality control Defect detection Document review Compliance checking Pattern detection Root-cause analysis AI-supported quality techniques Automated document inspection Predictive
• MODULE 15: AI for Procurement and Contract Management Procurement applications Requirements analysis Supplier evaluation Bid analysis Procurement risk Procurement forecasting Contract review Generative AI applications Contract summarization Clause identif
• MODULE 16: AI for Change Management Topics Change requests Change impact analysis Change prioritization Scope changes Schedule impacts Cost impacts Resource impacts AI applications
• MODULE 17: Predictive Project Management and Machine Learning This module moves beyond Generative AI. Machine-learning applications Schedule-delay prediction Cost-overrun prediction Resource-demand forecasting Project success prediction Risk prediction
• MODULE 18: AI Agents and Autonomous Project Management This is an important modern addition. AI agents What is an AI agent? AI assistant vs AI agent Agentic workflows Autonomous task execution Multi-agent systems Potential project-management application
• MODULE 19: CAPSTONE — AI-ENABLED PROJECT MANAGEMENT PLAN Participants select a real or simulated project and develop a complete AI-Enabled Project Management Strategy. The project should demonstrate how AI will be used across the project lifecycle, in

Schedule & fees