The AI Governance Practitioner Program: Course 3

Governance through the AI Lifecycle

Governance that only exists in policy documents doesn't govern anything. This course teaches you how to embed it directly into every stage of the AI lifecycle, using a mechanisms-based approach pioneered at Amazon.
Most governance frameworks tell you what to do at each stage of the AI lifecycle. This course shows you how to make it happen — through mechanisms: structured, closed-loop governance activities with defined inputs, outputs, controls, and inspection methods that sit inside your development and deployment processes rather than alongside them.

You'll work through all seven stages of the AI lifecycle from ideation to retirement, learning what governance activities belong at each stage and how decisions made in one stage cascade into the next. The 35+ exemplar Mechanism Cards give you a ready-to-adapt library built from real implementations — not templates invented for a textbook.

At 6.75 hours across 10 topics and 76 activities, this is the most technically detailed course in the Foundation Track. It maps to IAPP AIGP Domains 1B and IIIA.
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 The next course in The AI Governance Practitioner Program is Course 4: Writing AI Governance Policies
 Buy individual courses (US$59) or purchase Track 1: Foundations of AI Governance, including Courses 1 - 4, for US$199.

Level:

Practitioner

Inclusions:

10 Topics
74 Activities
35 Mechanism Cards

Time:

6.75 hours

(52 bite-size videos)

Maps to:

AIGP Domain I.B
AIGP Domain III.A

Your Guide

James Kavanagh

Extraordinary level of detail presented clearly.
Peter Douglas
AI Ethicist & Applied Philosopher · Former Lecturer, Monash University

What You'll Learn

Embed governance into the AI lifecycle — learn from practices in Amazon of how to build adaptive mechanisms that support and accelerate safe innovation without adding adding bureaucracy

Apply mechanisms thinking to AI governance

Understand how Amazon's approach to closed-loop mechanisms transforms governance principles into consistent, adaptive practice.

Govern across all 7 stages of the AI lifecycle

From ideation through development, deployment, and retirement, with specific activities and accountabilities at each stage.

Link organisational and system-level governance

Connect portfolio-level risk management to the stage-specific mechanisms that make governance scale.

Adapt 35 exemplar Mechanism Cards for your organisation

See how inputs, outputs, tools, adoption approaches, and inspection methods work together in practice, then build your own.

Course Outline

Your Guide

James Kavanagh

James Kavanagh is a globally recognised leader in AI Governance, known for designing and implementing governance frameworks that make AI safe, secure, and lawful in practice.

At Microsoft, he led the deployment of multiple Azure cloud regions worldwide, building governance mechanisms that scaled from infrastructure to security certification. At Amazon, he created and led the company’s first Responsible AI Governance Program, achieving one of the world’s first ISO 42001 certifications.

Today, as Founder and CEO of AI Career Pro, James helps professionals translate their existing experience into purposeful and rewarding roles in AI governance. He writes frequently to share his experiences and insights at blog.aicareer.pro.

He also leads the creation of Hooman, a platform that employs AI to help govern AI at scale through adaptive human oversight. Within the development lifecycle of Hooman, James and his team are testing every principle and framework taught in these courses in live, real-world systems. 

That’s the foundation of his philosophy: “We teach what we build, and we build what we teach.” Every course, case study, and tool in the AI Governance Foundation Program is grounded in real implementation experience - giving you access to the same methods used by leading organisations to govern AI safely, securely and lawfully.