Track 1. Course 2.

Organising for AI Governance

Learn how to align your organisation around clear, shared expectations for AI - defining the roles, responsibilities, and structures that make governance work in practice.

Building on the foundations from Course 1, this course shows you how to turn AI governance theory into action. You’ll explore how to bring multiple disciplines together, map your organisation’s AI systems from both business and technical perspectives, and define the principles and commitments that guide responsible AI into the future.

With ready-to-use templates, charts, and examples, you’ll gain the tools to embed AI governance across your organisation - confidently and effectively.

Write your awesome label here.

Level:

Foundation

Inclusions:

7 Topics
49 Activities

Time:

4.75 Hours

(48 bite-size videos)

Maps to:

AIGP Domain I.B

Your Guide:

James Kavanagh

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 and responsibilities

Learn to clarify ownership, accountability, and decision-making for AI systems, ensuring every stakeholder understands their part.

Build cross-functional collaboration

Discover how to bring legal, risk, data, and business teams together to build shared understanding and alignment.

Map your AI systems

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

Establish AI principles and commitments

Translate organisational values into measurable principles using the AI Principles Canvas, creating alignment and accountability across all AI initiatives.

Write your awesome label here.

Write your awesome label here.

Write your awesome label here.

Write your awesome label here.

Write your awesome label here.

Write your awesome label here.

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.