Generative AI and Agentic AI for Project & Program Management

Gen AI is what you use when you prompt a tool to help you do something — drafting a charter, analysing risk, writing a stakeholder update. Agentic AI is what runs in the background doing those things continuously without you prompting it each time — a risk monitoring agent that reads every project communication, a reporting agent that generates the weekly status pack automatically. Both are real, both are available now, and both are covered in every module so you understand where to use each one in your actual work.

No coding, no technical setup, and no specific tool experience required. The course uses ChatGPT and Claude — both accessible through a browser with a free account. If you can write an email and use a browser, you have everything you need. The AI Foundations course (4 hours) is the only prerequisite.

Yes — the course is specifically built for PMs, Scrum Masters, and Program Managers. Scrum Masters will find direct application in the modules on sprint execution, retrospectives, standup management, stakeholder communication, and risk identification from team signals. The agentic workflows covered — including meeting agents that auto-generate action items and risk agents that monitor team sentiment — are particularly relevant to the Scrum Master role.

The course awards 24 PDUs and 24 SEUs upon completion. PDUs are categorised under Education — Technical, which counts toward PMP and CAPM renewal with PMI. SEUs count toward CSM and other Scrum Alliance credentials, as well as SAFe certification maintenance. PMI’s own CPMAI certification (Certified Professional in Managing AI) also accepts relevant AI training toward its requirements. Always verify the current requirements with your specific certification body, but for most PMI and Scrum credentials this course qualifies directly and covers a significant portion of a full renewal cycle.

The course uses ChatGPT (free tier is sufficient for most exercises), Claude (free tier available), and Otter.ai for meeting transcription demonstrations. No paid subscriptions are required to participate fully. The prompt library and techniques taught work across any large language model, so if your organisation uses Microsoft Copilot, Google Gemini, or another tool, everything transfers directly.

Real deliverables, built during the course using a realistic project scenario. The six projects are: an AI-generated charter, stakeholder map, and risk register; a WBS, schedule baseline, and EVM budget projection; a vendor evaluation matrix and SOW first draft; a change request impact analysis and stakeholder communication package; a leadership dashboard and AI-generated status report; and a lessons learned document and personal 90-day AI adoption roadmap. These are the actual documents a PM produces on a project — the course just shows you how AI helps you produce them in a fraction of the time.

With the right prompting — yes, consistently. The course teaches you exactly how to structure prompts so AI produces outputs that require minimal editing before they are presentation-ready. You remain accountable for the content and make the final call on every deliverable — AI drafts, you review and refine. The course includes specific modules on EVM narrative generation, leadership status reports, and stakeholder communications, with real examples of the before-and-after quality difference that structured prompting produces.

Free content shows you individual tips and tool demos. This course builds a complete, structured methodology across the full PM lifecycle — with both Gen AI and Agentic AI covered in every phase, 200+ tested prompts organised by PM activity, 6 real deliverables you complete during the course, and live instruction where you can ask questions in context. The difference is between knowing AI exists and knowing exactly how to use it for every type of PM work you do every week.

Yes. The course teaches AI techniques and prompt approaches that are tool-agnostic — they work whether your team uses Jira, Asana, MS Project, ClickUp, or any other PM platform. You will also learn how to use AI alongside your existing tools: extracting data from them, generating inputs for them, and in some cases using AI to interpret and analyse data from them. The goal is to make AI work within your current environment, not to replace it.