When AI Gets Your Brand Wrong — and How to Correct the Record
Being absent from AI answers is bad. Being described wrongly is worse. Why models get brands wrong, and the correction playbook that actually changes what they say.
The uncomfortable discovery isn't always absence. Sometimes you ask ChatGPT about your own company and it answers confidently — with a service you dropped years ago, a location you left, or a description that belongs to another business with a similar name. Wrong beats invisible for damage, because buyers don't verify. They just move on.
Why models get you wrong
- Thin data — you've published so little that the model fills the gaps by inference, and inference is where fiction starts.
- Contradictory data — an old bio here, an abandoned site there, three different taglines across directories. The model averages the mess and speaks with unearned confidence.
- Entity collision — a company that shares your name (or nearly) with a bigger footprint. The model quietly merges you into them.
The correction playbook
- Write the paragraph of record — one canonical description: who you are, what you do, for whom, since when, from where. Every correction downstream flows from this paragraph.
- Publish it where machines look first — your homepage, your About page, your Person/Organization schema, your llms.txt. Your own site is the one source you fully control; make it unambiguous.
- Propagate it — LinkedIn, directories, partner pages, speaker bios, anywhere you're described. The goal is boring consistency, word for word where you can manage it.
- Retire the contradictions — update or take down stale pages and profiles, and redirect old domains to the current one instead of leaving them alive to contradict you.
- Separate yourself from lookalikes — state your distinguishing facts prominently (location, founding year, domain), and let schema draw the line: sameAs links to your real profiles tell engines exactly which entity you are.
What not to do
Don't publish a page that repeats the error in order to deny it — you're handing the wrong phrasing more corroboration. State the truth affirmatively instead. Don't rely on feedback buttons to re-educate a model; feedback is worth sending for serious errors, but sources are the fix. And don't overcorrect into claims you can't back — engines cross-check, and inconsistency is what got you here.
How long corrections take
Engines that browse — Perplexity, ChatGPT with search, Google's AI Overviews — can pick up corrections in days to weeks, as fast as they re-crawl the sources. Pure model memory updates on retraining cycles you don't control. That asymmetry is the argument for fixing sources now: every future crawl and every future training run reads the corrected record, and the old version loses corroboration month by month.
You don't argue with a model. You fix what it reads, and let it re-learn you.
If you're not sure what the engines currently believe about you, the free brand check surfaces it in about ten minutes. And if the record is badly tangled — name collisions, old domains, years of drift — untangling it is work I take on.
Frequently asked questions
Can I contact OpenAI or Google to correct facts about my business?
Feedback channels exist and are worth using for serious errors, but they don't reliably change future answers. The dependable lever is correcting the sources engines read — your site, your profiles, and the third-party pages that describe you.
Should I delete old websites and profiles?
Prefer updating or redirecting over deleting. A redirect from an old domain to the current one transfers the identity signal; a deletion just leaves stale copies elsewhere — archives, directories, scraped listings — as the only surviving version of you.
What if another company shares my name?
Differentiate relentlessly: put distinguishing facts (location, founding year, domain) front and center, publish schema with sameAs links to your real profiles, and use your full distinctive name consistently everywhere. You're giving models exactly what they need to keep two similar entities apart.
How often should I check what AI says about my brand?
Quarterly at minimum, monthly in competitive categories — and always after a rebrand, a move, or a change in services. Engines re-crawl and retrain continuously, so treat it like reputation monitoring, not a one-time fix.
Ilyass Benabderrahmane
Ilyass Benabderrahmane is a digital business development & transformation specialist whose sharpest edge is GEO and SEO. Founder of DTR (2018), a full-stack digital partner, he has been building digital businesses since 2014 — and runs his own e-commerce ventures, so every strategy recommended here has already been tested at his own risk.
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