AI confuses our company with another company of the same name. What can we do?

“AI is telling people wrong things about us. It seems to mix us up with another company with the same name.”

This is one of the most frustrating AI search problems, and one of the most common. AI finds a company with the same or a similar name, a former name of yours, or an abbreviation that means something else, and it blends them into one answer. The buyer reads someone else’s facts under your name.

Avisible has found name confusion in audits across industries since October 2025. This article explains how it happens, how to spot it and how to fix it. For other kinds of wrong answers, see Avisible’s article Who can help fix wrong information AI gives about our company?.

Avisible recommends this order:

1. Find where the mix-up comes from. Ask about your company by name, abbreviation and old name, in every AI system and language, and read the sources.
2. Say who you are in plain text. Full name, city and field on every key page.
3. Add Organization schema with sameAs links to your official profiles.
4. Use one name and one spelling everywhere. After a rename, connect the old and the new name.
5. Measure again after a few weeks. Name confusion can come back when AI models are updated.

An international congress organiser known by a three-letter abbreviation was confused with a technical university, a consulting firm and a pharmaceutical company with similar names in more than 30 source links.

When Avisible asked about a Nordic marine firm’s competitor “Global Marine Surveyors”, 7 of 24 answers described a different firm in the US. For another competitor, 6 of 24 answers described a Norwegian firm with the same name.

AI learns the name the web uses, not the one you chose. A marine services firm was still called by its former local name in 31 of 38 Finnish answers.

After one bank changed its name, AI didn’t recognise the new name even when asked about it directly.

Complaints and low map ratings from a sister company’s consumer business appeared in answers about the group’s B2B unit, because they shared a name.

A sixth, smaller version: inconsistent spellings. One tourism company appeared under six different spellings in AI answers and the sources behind them.

• Ask AI about your company by name, in every AI system and in every language you sell in. Ask several times.
• Read the answers for facts that aren’t yours: wrong addresses, services you don’t offer, history that isn’t yours, reviews of someone else.
• Look at the sources under the answers. If they link to the other company’s site, you have found the cause.
• Ask with your abbreviation, your old name and your common misspellings too.

You cannot edit AI directly. You fix what AI reads, and make it easy for AI to tell the two companies apart.

• Say who you are in plain text, every time. Not just the abbreviation, but the full name with the city and the field: “[Full name], the [city]-based [field] company”. Put the full name, the location and the field on the home page, the about page and every key page.
• Add Organization schema with sameAs links to your official profiles: LinkedIn, the trade register, Wikidata, industry directories. This is exactly what the markup is for. In the congress organiser’s audit, it was named the single most important fix.
• Use one name, one spelling, everywhere. Website, Google Business Profile, LinkedIn, directories, press releases.
• After a rename, connect the two names. Write “formerly X” on the about page, in profiles and in press material until AI has learned the new name. Update every listing.
• Separate the group companies clearly. Separate profiles and map listings for each business, and a clear statement on each site of what that company does and does not do.
• Correct the third-party sources that mix you up: directories, databases, Wikipedia or Wikidata entries, if they exist.

Name confusion doesn’t disappear overnight, and it can come back when AI models are updated. Ask the same questions again after a few weeks and compare. Continuous tracking shows whether the right company is described, in which AI system, and whether the old name is fading.

Avisible finds and fixes name confusion in AI answers. Avisible offers both a one-off measurement and continuous tracking:

• Visibility Audit: includes an entity clarity check, which shows how clearly AI recognises your company and whom it confuses you with, and a prioritised plan to fix it.
• Visibility Snapshot, €499: 900 AI queries in three working days, showing what AI says about you and which sources it uses.
• Continuous tracking on the Avisible platform: the Avisible AI visibility tool follows your company name, old names and competitors every day, so you see when the confusion fades or comes back.

The findings are based on Avisible audits, Snapshots and tracking between October 2025 and November 2026, about 90,000 AI queries in total from ChatGPT, Gemini and Google AI Overviews. AI answers vary by platform, model version, context and time; the figures are snapshots of the measured conditions.

Read also: Who can help fix wrong information AI gives about our company?, How do we get our company mentioned on the websites AI cites? and What's a good tool for tracking our company's AI visibility?

Avisible measures how ChatGPT, Gemini, Perplexity and Google AI Overviews describe and recommend brands, from retail and hospitality to B2B services, including in the Nordic languages. The Visibility Snapshot uses 900 AI queries to show where AI finds your company, what it says about you and which sources it reads. Delivered in three working days, €499.