AI for Project Management

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Course Overview

The future of project management lives at the intersection of human creativity and technological leverage. This immersive, hands-on three-day course prepares experienced project professionals for an AI-empowered future — equipped with actionable strategies and a set of working artifacts you build live, not just notes you take.

Designed for experienced project managers in enterprise environments, the class covers what generative AI can and can't do, how to prompt it well, and where it fits across the project lifecycle. You'll work a single realistic case study from first principles through to a final adoption plan, practicing in a persistent team throughout.

Along the way you'll build a prompt playbook, a prioritized use-case map, planning and lifecycle deliverables, an ethics-and-governance audit, and both a team adoption plan and a personal development roadmap. By the end of Day 3, you'll be ready to apply an AI-enabled project management approach across any framework or toolset.

Important Note: All students will need access to at least one generative AI tool during class (ChatGPT, Claude, CoPilot, or Gemini)

Who Should Attend

This course is ideal for Project Managers, Program Managers, and Product Managers

Course Objectives

• Explain what LLM-based generative AI can and can't do — and recognize the "confidence trap" before it costs you.
• Prompt effectively using a structured, iterative approach (the COSTAR framework).
• Identify and prioritize AI use cases with an automation / augmentation / transformation lens and a feasibility-impact matrix.
• Evaluate AI tooling — embedded, standalone, and private LLMs — using the DVF (Desirability, Viability, Feasibility) framework.
• Apply AI across the project lifecycle in both predictive and adaptive environments.
• Use AI for data analysis, validation, summarization, and information retrieval — and verify its output.
• Manage ethics, bias, disclosure, data privacy, and compliance in AI-assisted projects.
• Build a team AI adoption roadmap grounded in change-management practice (the adoption curve, ADKAR, SMART goals, and ROI).
• Leave with a personal 30/90-day development roadmap to sustain momentum after class.

Course Outline