5 posts with this tag
In the AI era the in-house-versus-agency decision is no longer mainly about cost. Keep the layers that compound — brand judgement, first-party data, and the client memory that makes AI improve — and use agencies for elastic production and specialist execution. The deciding question moved from price to compounding.
Governing marketing data for AI comes down to four decisions you make before the model sees anything: what it may see, where it may run, who owns the output, and how long you keep it. Teams that build the memory layer first and govern later end up rebuilding it under a lawyer's supervision.
A marketing AI policy says what AI may touch, who reviews it, and what data it can see. Governance is how you make those rules real. Policy without enforcement is a document nobody follows; governance without policy is enforcement with nothing to enforce.
AI changes brand safety in paid media in two ways: it multiplies the creative and copy that can misrepresent the brand, and it makes placement and context harder to judge at scale. The control is not a stricter blocklist. It is a review gate and a set of brand rules the models work inside.
An AI centre of excellence in marketing is a small team that owns standards, shared tooling, and capability while the rest of marketing uses them. Its job is enablement, not gatekeeping. The model usually worth building is hub-and-spoke, not a central team that approves everything.