The AI Governance Practitioner Program: Course 2

Organising for AI Governance

Most AI governance training tells you what good governance looks like. This course shows you how to build it - inside a real organisation, with real constraints, across teams that don't naturally work together.
There's a gap between knowing AI governance principles and being able to implement them. Roles need to be defined and owned. AI systems need to be mapped. Principles need to move from values statements into commitments that people can actually be held to. Cross-functional teams - legal, risk, data, engineering - need to work from shared understanding, not parallel frameworks.

This course works through all of it. You'll leave with a working structure for your organisation - not a theoretical model.

It builds directly on Course 1, but if you're already working in AI governance and need the organisational layer, it also stands on its own.
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 The next course in The AI Governance Practitioner Program is Course 3: Governance Through the AI Lifecycle.
 Buy individual courses (US$59) or purchase Track 1: Foundations of AI Governance, including Courses 1 - 4, for US$199.

Level:

Practitioner

Inclusions:

7 Topics
49 Activities

Time:

4.75 Hours

(48 bite-size videos)

Maps to:

AIGP Domain I.B

Your Guide:

James Kavanagh

This is an extremely practice-oriented course. The course content and additional reference links actually help to build up my practical knowledge.
Brijesh NelliyattKariyil
CISSP | CRISC | AIGP · Cybersecurity & AI Governance Professional

What You'll Learn

Turn governance theory into action — learning how to organise, align, and operationalise AI governance across teams, systems, and principles.

Define roles, ownership, and accountability

Clarify who is responsible for AI systems, who is accountable for governance decisions, and how to make that stick across the organisation.

Map your AI systems

Use practical templates to build business and technical inventories of your AI systems, including datasets, models, and interfaces.

Build cross-functional collaboration

Bring legal, risk, data, and engineering teams into shared understanding and aligned practice.

Establish AI principles and commitments

Translate organisational values into specific, testable AI principles using the AI Principles Canvas.

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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 Practitioner 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.