GenArchitects Academy

Leading AI Projects & Teams

Categories: Business & Leadership
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🔒 This course unlocks after AI Foundations

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About Course

👋 A welcome from your AI strategist

AI projects fail far more often from planning and adoption problems than from the technology. This course gives you the delivery playbook: stage gates, honest estimates, AI-specific risk and governance, and leading people through change.

Work through it at your own pace, try every practice task before opening the model answer, and look for my 🏛 Architect’s Notes along the way.

Mahesh Raja Vandyala
AI Strategist and Enterprise Architect · LinkedIn

AI for Project Managers teaches you to deliver AI initiatives that actually reach production and get used: planning uncertain work with time boxes and stage gates, estimating the hidden work, managing AI-specific risks and governance, leading people through change, and using AI to speed up your own PM work.

You follow a running case study: Ryan Cooper, Project Manager at Nimbus Freight, a fictional logistics company, as he delivers two AI pilots from approval to adoption.

What makes this course different

  • Worked examples: real gate papers, estimates, risk registers, status reports and go-live checklists
  • Downloadable templates: stage-gated project plan, AI risk register, RACI, status report, use-case register and evaluation set
  • Practice tasks with model answers, scenario-based quizzes, and Architect’s Notes from practitioners
  • A portfolio-grade capstone with a scoring rubric

Part of the Project Managers learning path, alongside the 3 common courses: AI Foundations, Prompting & AI Productivity, and Responsible AI. Two modules are shared with the Business Analysts path, so you see how PMs and BAs work together on AI.

Last reviewed: November 2026

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Course Content

Module 1 — How AI Projects Differ
Why AI projects are experimental, data-dependent and never "done", and what that means for delivery.

  • 1.1 Why AI Projects Behave Differently
  • 1.2 The AI Project Lifecycle
  • 1.3 Who Does What on an AI Project
  • Module 1 Quiz: How AI Projects Differ

Module 2 — Finding & Prioritising AI Use Cases
Discover AI opportunities with stakeholders, size them, and build a prioritised portfolio.

Module 3 — Planning & Estimating Uncertain AI Work
Time-boxed experiments, stage gates, and plans that hold up when the results are uncertain.

Module 4 — AI Risk, Governance & Compliance in Delivery
Run an AI risk register, build in governance checkpoints, and keep the project compliant.

Module 5 — Evaluating AI Outputs & Vendors
How to judge whether an AI solution is good enough, and how to compare vendors fairly.

Module 6 — Leading Teams Through AI Adoption
Change management for AI: addressing fear, training, champions and measuring adoption.

Module 7 — AI for Your Own PM Work
Use AI to plan, report, manage risk and run meetings, saving hours every week.

Capstone — AI Project Delivery Pack
A portfolio-grade delivery pack: charter, stage-gated plan, RACI, risk register, governance, adoption plan and status report.

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