Course Description

This one-day course introduces how artificial intelligence (AI) can enhance modern project management practices. Participants will explore how AI tools can support planning, communication, risk management, and performance tracking. Through practical examples and guided exercises, learners will discover how to use AI to improve efficiency, decision-making, and collaboration across the project lifecycle.

The course balances core project management principles with applied AI use cases, ensuring participants leave with actionable techniques they can immediately apply in their roles.

Target Student

Project Managers, Project Coordinators, PMO staff, Team Leaders, Operational Managers, Business Analysts, Change Managers, and anyone involved in delivering projects who wants to leverage AI tools. No prior AI experience is required.

Pre-requisites

• Basic understanding of project management concepts (e.g. planning, risks, stakeholders)
• Familiarity with workplace productivity tools (e.g. email, documents, spreadsheets)

Core Learning Objectives

• Explain how AI can support project management processes
• Use AI tools to assist with project planning and documentation
• Apply AI to improve communication and collaboration across teams
• Identify how AI can support risk and issue management
• Use AI to monitor project progress and generate insights
• Write effective prompts to get better outputs from AI tools
• Recognise the limitations and risks of using AI in projects

Course Outline

1. Introduction to AI in Project Management

• Overview of AI and its role in the workplace
• How AI is transforming project management
• Introduction to common AI tools and capabilities
• Key benefits: productivity, automation, insights, collaboration

2. Foundations of Effective AI Use

• Understanding how AI tools work in a project context
• Writing effective prompts for better outputs
• Customising and refining AI-generated content
• Limitations, risks, and ethical considerations of AI use

3. AI for Project Planning

• Generating project plans, tasks, and timelines
• Drafting project documentation and reports
• Using AI to support resource and budget planning
• Applying lessons learned and historical data
• Practical application: creating a project plan with AI

4. Enhancing Communication with AI

• Drafting and refining project communications
• Summarising emails, documents, and updates
• Creating clear and consistent stakeholder messaging
• Reducing time spent on routine communication tasks

5. AI for Collaboration and Team Working

• Supporting collaboration across distributed teams
• Using AI to summarise meetings and track actions
• Improving alignment and coordination
• Integrating AI with collaboration tools (e.g. chat, meetings, shared documents)

6. Risk and Issue Management with AI

• Identifying and analysing project risks using AI
• Using AI to highlight trends, gaps, and priorities
• Generating risk insights and key management questions
• Understanding AI limitations (data quality, human oversight required)

7. Monitoring Progress and Performance

• Tracking project progress using AI tools
• Generating status reports and summaries
• Identifying delays, risks, and performance issues
• Using AI for data-driven decision making

8. Practical Application and Case Study

• Applying AI across the project lifecycle
• End-to-end scenario: planning, communication, risk management, and monitoring
• Group exercises and discussion

9. Embedding AI into Project Practice

• Best practices for adopting AI in projects
• Change management considerations
• Building confidence and capability in teams
• Next steps and continued learning