Model
AI governance that speeds work up
Short answer: AI governance in marketing is six things — a one-page policy, clear data rules, brand safety encoded in shared assets, human review scaled to risk, a named owner, and a light audit trail. Done well it removes hesitation instead of adding process.
Klicka dig igenom delarna. Det här är strukturen jag sätter upp innan ett team börjar producera i skala med AI.
One page people will actually read
An AI policy for marketing teams should fit on a page: what AI may be used for, what it may never be used for, and what has to be disclosed. Long policies get ignored, short ones get followed.
Test: can a new hire summarise the policy after one read?
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What happens without it
- Shadow use: people use AI anyway, on private accounts, with company data.
- Output drift: everything sounds slightly off-brand and nobody can say why.
- Approval paralysis: legal blocks everything because nothing is documented.
- Stalled adoption: teams wait for permission that never formally arrives.
How I roll it out
- Write the one-pager with legal in the room, not after the fact.
- Approve a small tool list, and say plainly what is not approved.
- Build shared prompts and brand references so the safe path is the fast path.
- Train on real briefs, then review after a month and adjust.
If your team is using AI without a written rule, you already have a governance model. Just not one you chose.
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