A practical approach to identifying the right problems to work on
A practical approach to identifying the causes of governance problems, and then design the right fixes
Introducing the AI Career Pro Foundations Cohort and Foundations Practitioner Award
What the data from hundreds of practitioner assessments tell us about the transitions that define an AI governance career.
Introducing a practical framework for measuring your practitioner capability and organizational capacity to govern AI. Take the assessment and find out where you stand.
Real AI governance needs both practitioner capability and organisational capacity, built together through messy practice. Stop waiting. Start building, start learning, and design your governance to evolve alongside the systems it is meant to govern.
We have more frameworks, standards, principles, and conference panels than ever. What we don't have is enough organisations with capacity to govern their AI systems, and enough capable practitioners to do the work.
A practical guide to achieving the IAPP AIGP Certification in 21 days using the AI Career Pro Exam Prep course, by precisely focusing on the 2026 IAPP Body of Knowledge v2.1.
Why writing your AI governance policy by transposing straight from a regulation, standard or framework is a shortcut to failure. And what you can do instead.
As an engineer reading the EU AI Act, I see so many requirements that look rational in isolation, but put together are incoherent and disconnected from the reality of AI systems in use.
The gap between compliance documentation and genuine system-level assurance is where AI governance is falling down. Other industries learned this lesson the hard way.
Most writing about AI governance begins with failure. This article begins with the most impressive safety record of any autonomous system, and asks what approach to governance makes it possible.
FREE Introductory Course
Doing the Work of AI Governance
