A practical introduction to using artificial intelligence to enhance project management outcomes, breaking down complex AI concepts and outlining actionable steps for integrating AI into everyday project workflows.
Overview
Syllabus
Module 1: AI 101 for Project Managers
- Define artificial intelligence and distinguish narrow vs. general AI
- Introduce core concepts: natural language processing (NLP), machine learning (ML), and generative AI
- Debunk common myths and set realistic expectations for AI capabilities and limits
Module 2: Why AI for Project Management
- Examine how AI is changing the modern workplace and project environments
- Map AI-enabled skills to PMI’s Talent Triangle® (Ways of Working, Power Skills, Business Acumen)
- Identify future-readiness steps for managing projects alongside AI tools
Module 3: AI Applications for Project Management — Planning
- Use AI to clarify project charters, scope statements, and WBS drafts
- Leverage AI for requirements gathering, stakeholder analysis, and risk identification prompts
- Apply AI-assisted estimation and scenario exploration to inform baselines
Module 4: AI Applications for Project Management — Scheduling, Risk, & Communications
- Generate schedule drafts, dependencies, and what-if analyses with AI assistants
- Strengthen risk analysis with pattern detection, probability cues, and mitigation optioning
- Enhance reporting and stakeholder communications with AI-written summaries and visuals
Module 5: Ethical, Legal, and Practical Considerations
- Address bias, privacy, transparency, and data provenance in federal contexts
- Define appropriate human-in-the-loop controls and oversight
- Align usage with federal AI guidance, policies, and compliance requirements
Module 6: Preparing for AI Integration
- Create a strategy for selecting, piloting, and scaling AI use cases
- Develop a communication plan for stakeholders, leadership, and teams
- Incorporate change management, training, and governance into rollout plans