The AI Governance Gap in Marketing
Marketing teams have adopted AI tools at a pace that far outstrips their governance frameworks. Content generation, audience segmentation, predictive analytics, automated personalisation — these capabilities are powerful, but each introduces data protection considerations that most organisations haven't addressed.
The EU AI Act is now in force, and while many of its provisions target high-risk systems, marketing uses of AI are not exempt from scrutiny. Profiling, automated decision-making, and the use of personal data in training models all carry regulatory implications.
Why Marketing Needs Its Own Framework
Generic AI governance policies, usually written by IT or legal, rarely account for the specific ways marketing teams use these tools. A marketing-specific framework needs to address:
Data Inputs
What personal data feeds into your AI systems? Customer behavioural data, CRM records, website analytics, social media interactions — each has its own legal basis requirements and retention considerations.
Model Transparency
Can you explain how your AI tools make decisions? When a tool segments an audience or scores a lead, the logic needs to be explainable, both for regulatory compliance and for maintaining trust with your audience.
Output Review
AI-generated content, recommendations, and targeting decisions should be reviewed before deployment. This isn't about slowing things down — it's about catching the edge cases where automated systems produce biased or non-compliant outputs.
A Practical Starting Point
Rather than attempting a comprehensive framework from day one, start with three actions:
Map your AI inventory. Document every AI tool your marketing team uses, what data it accesses, and what decisions it influences. Most teams are surprised by how many tools they're actually using.
Establish review checkpoints. For high-impact uses like audience profiling and automated personalisation, build human review into the workflow. This doesn't need to slow you down — it needs to be systematic.
Create clear escalation paths. When a team member encounters an AI output that seems problematic, they need to know exactly who to raise it with and what happens next.
Looking Forward
AI governance in marketing will only become more important. The organisations that build frameworks now — even imperfect ones — will be far better positioned than those waiting for regulatory clarity that may never come in the form they expect.
The goal isn't to restrict AI adoption. It's to adopt it in a way that's sustainable, compliant, and maintains the trust you've built with your audience.