Why every organization needs a RACI Matrix
As AI systems become increasingly integrated into critical business processes, ensuring accountability is no longer optional. But assigning responsibility in a multidisciplinary, high-stakes environment like AI development is far from straightforward.
Who approves a new model for production? Who signs off on compliance with the EU AI Act? And who ensures proper monitoring once the system is live?
This is where a RACI matrix becomes indispensable.
A RACI (Responsible, Accountable, Consulted, Informed) matrix helps organizations define clear ownership across all stages of the AI lifecycle, from model development and validation to deployment and audit. It clarifies who is in charge of what, avoids duplication or gaps, and ensures that governance processes scale effectively as AI adoption grows.
This matrix is part of our broader practical guide to AI governance, where we’ve outlined a role-based operating model tailored to real-world needs. Our RACI matrix reflects this approach and is designed to be both robust and lightweight, supporting organizations whether they are just beginning to formalize their governance or are scaling mature AI systems.
Download the RACI matrix here to see how roles like the AI Owner, Validator, and Compliance Officer fit together in a practical governance setup.
Download RACI Matrix
Author
Jos Gheerardyn has built the first FinTech platform that uses AI for real-time model testing and validation on an enterprise-wide scale. A zealous proponent of model risk governance & strategy, Jos is on a mission to empower quants, risk managers and model validators with smarter tools to turn model risk into a business driver. Prior to his current role, he has been active in quantitative finance both as a manager and as an analyst.