What goes wrong?
A common pattern: a company's product page says a service is available in two markets. An old distributor profile, written years ago, says it's available across a whole region. A buyer asks an AI assistant who offers the service in their country, and the answer names the company with the broader claim attached.
Nobody at the company wrote anything wrong this year. But now a salesperson has to walk a prospect back from something the prospect believes, and that conversation starts with the company looking less reliable than it is.
Why can't marketing just fix it?
Because most of the facts don't belong to marketing. What the product does, and where, belongs to the product team. What a regulated business may claim belongs to legal or compliance. What a partner says about you sits on the partner's website. Marketing can spot the problem, but it can't approve the fix, and often can't publish it either.
So the problem goes around in circles. Marketing raises it, product says the page is correct, and the old partner profile stays up.
Who should own what?
In companies that handle this well, the roles are clear:
The CMO
decides which buyer questions matter most, and signs off the list of issues to fix.
Product
confirms what's true for each product, market and version.
Legal or compliance
approves any claim with regulatory weight.
The digital team
publishes corrections on the company's own pages.
Partnerships or communications
asks third parties to update what they've published.
Whoever runs the audit
records what the AI said, and checks again after changes.
None of this needs a new department. It needs one shared issue log, and a name next to each fact.
What does a fact register look like?
It's a simple table. For each fact that buyers care about, record the approved wording, which market and product version it applies to, the page where it lives, who approved it and when it's next due for review. When an AI answer gets something wrong, add the exact question, the answer, the date and the source it drew on.
Then sort by consequence. A slightly odd description is low priority. A wrong statement about availability, eligibility, pricing conditions or exclusions goes to the top, and in regulated businesses it follows your existing risk process.
What does a good monthly rhythm look like?
Three short lists, reviewed once a month:
Errors that matter
wrong facts in AI answers that could change a buyer's decision.
Missed shortlists
questions where you're a genuine fit, but AI names someone else.
Stale sources
your own pages, PDFs and partner listings that are out of date.
Each item has an owner and a date. After changes go live, ask the same questions again and record what changed, and what didn't.
What can you control, and what can't you?
You can correct the information you publish, and ask others to correct theirs. You can't edit what an AI model says directly, and a corrected page won't always change an answer the same week. So report the two things separately: what you fixed in public, and what the answer says now.
Frequently asked questions
Can we ask ChatGPT to correct what it says about us?
Some platforms have feedback routes, and they're worth using for serious errors. The lasting fix is correcting the sources the answers draw on.
Who should own AI visibility overall?
One sponsor, usually the CMO, with product, compliance and digital each owning their part of the facts.
How often should we check?
Monthly for the questions that matter most, plus a check after any significant product or pricing change.