How to Find Competitors in Google AI Overviews

To find competitors in Google AI Overviews, run your target queries in a clean browser, record every brand named and every domain linked in the overview, then repeat the run several times because the answer changes. A tool automates this: Semrush and Ahrefs read Google's results, and Noma by Nurdd tracks named brands across engines.

Key takeaways

• Google Search Console does not list competitors. It rolls AI feature traffic into the Web search type, so you must look at the overview itself.
• Record two things per query, not one: brands named in the text and domains cited in the links. They often differ.
• One check is not enough. Ahrefs reports a 70% chance that an AI Overview changes between observations.
• Start with 20 to 30 queries tied to buying decisions, and run each at least three times before you call anyone a competitor.
• Your AI Overview competitors are often not your organic competitors. Build the list from the answers, not from your rank tracker.

Which competitors show up in AI Overviews, and why they differ from your SERP rivals

An AI Overview is a generated summary above the classic results, and it links to the pages it drew on. Google's documentation says AI Overviews and AI Mode may use "query fan-out", issuing several related searches to build one response, so the pages it cites can come from subtopics your target keyword never mentions.

That is why the list of rivals changes. A thruuu analysis published in thruuu, August 2026 says 68% of Google AI Overviews cite pages that do not rank in the organic top 10. We have not verified how thruuu measured that, so treat it as a vendor claim. The practical point stands without it: a rank tracker will not tell you who is being cited.

Two kinds of competitor matter, and they need separate columns in any sheet you keep.

How can I see which competitors appear in Google AI Overviews by hand?

The manual method costs nothing and gives you a baseline before you pay for anything. It also shows you what a tool should be reproducing, which helps you judge its output.

Step 1: Build a fixed query list

Pick 20 to 30 queries a buyer would type before choosing a supplier: category terms, "best X for Y", comparisons and problem questions. Pull candidates from Search Console's query report and People also ask. The free Noma AI Prompt Finder lists questions buyers ask about a category, tagged by intent, which is a quick way to fill gaps. Freeze the list. Changing wording between runs ruins comparisons.

Step 2: Control the conditions

Use a private window, signed out, with the country and language of your buyers. Note the date, device and location in the sheet. AI Overviews do not appear for every query: Google says they show only when its systems judge them additive to classic Search, so a blank result is data too, not an error.

Step 3: Record what you see

1. Query and date.
2. Did an AI Overview appear (yes or no)?
3. Brands named in the text, in order of appearance.
4. Domains linked, with the exact URL.
5. Whether your brand is named, linked, both or neither.

Step 4: Repeat and tally

Run each query three times on different days. Ahrefs, October 2026 states that AI Overviews have a 70% chance of changing between observations, that content lasts about 2.15 days, and that 45.5% of cited sources are entirely new each time. A single screenshot is therefore an anecdote.

Then tally. For each brand, count the share of runs in which it appeared, out of runs where an overview appeared.

A worked example of the tally

The numbers below are invented to show the arithmetic, not real data. You track 20 queries and run each three times: 60 runs. An AI Overview appears in 36 of them. Brand A is named in 18 of those 36 runs, which is a 50% mention rate. Brand B is named in 9 (25%). Your brand is named in 4 (11%) and linked in 12 (33%).

The reading: you are cited more than you are named. Engines use your pages but do not credit your brand in the text. That points to a positioning fix (clear brand statements near the facts) rather than a content-volume fix. Without the two columns you would not see it.

Which SEO tools track AI Overviews competitors?

Several SEO suites now report on AI Overviews. The table compares what each vendor says on its own page, as checked on 2026-10-31. It describes scope, not quality; run the same ten queries through any tool and compare with your manual sheet before you trust it.

Semrush's own guide gives a sense of scale for its data. It reports that canva.com ranks for 863K keywords with an AI Overview on the page (as of August 2026) and sits inside 156.3K of those overviews, per Semrush, August 2026. The gap between those two numbers is the point: having an overview on your SERP is not the same as being in it.

How to pick, in one pass

What do you do with the competitor list once you have it?

A list is only useful if each name leads to an action. Work down these four checks.

1. Read the sentence that names them. What claim is attached: cheapest, easiest, enterprise? That is the position you need to challenge.
2. Open the cited page. Is it their own site, a review site, a Reddit thread, a news article? A third-party source means the fix is earned coverage, not a rewrite of your page.
3. Compare against your page. Does yours state the fact in plain text, high up, with the same details? Google says "There are no additional requirements to appear in AI Overviews or AI Mode", so the fix is ordinary SEO quality: indexable, snippet-eligible, clear text.
4. Check eligibility. A page must be indexed and eligible for a snippet to be a supporting link, per Google Search Central. The free Noma AI SEO Checker runs 30+ checks on whether your site can be read by Google AI and other assistants, and lists the top fixes.

For a side-by-side of your Google rank and what Google's AI features cite for the same query, the free Google Rank vs AI Mode Checker is a quick cross-check.

Why clicks alone will not show you the competition

Search Console reports AI feature traffic inside the Web search type, and Semrush notes that this makes AI Overview clicks and impressions hard to pull out of overall data. Competitors are invisible there by design: it is your data only.

The stakes are real. Ahrefs reports that, on December 2025 data, AI Overviews reduce clicks to the top-ranking pages by 58%, per Ahrefs, October 2026. If a rival is named in the overview and you are not, the click you would have earned may never be recorded as a loss. Only a visibility measurement shows it.

How does Noma track which brands are named for your prompts?

Noma by Nurdd is an AEO (answer engine optimisation) and AI visibility platform. It asks 13 AI engines, including ChatGPT, Gemini, Perplexity and Claude, the questions your buyers ask, every day, and shows where your brand is named, where competitors are named instead, and which pages the answers cite. Google AI Overviews is one of those engines. Noma is not a keyword rank tracker, so it does not map every keyword's SERP features. It measures the prompt-level answer. Check the pricing page for which engines each plan covers.

See it on your own brand: book a demo or start the 3-day free trial. A card is taken at signup so billing can start on day 3; cancel before then and nothing is charged.

Why cross-engine data matters for this question

Engines disagree. A rival that Google names may be absent from ChatGPT, and the reverse. Noma's analysis of why engines disagree explains why averaging hides this, and the prompt tracking page describes the fixed prompt set, run daily from fresh sessions, that keeps comparisons clean. For the formula behind the numbers, see what AI share of voice is and how it is calculated.

Common mistakes when you find competitors in Google AI Overviews

• Trusting one screenshot. The answer changes within days.
• Logged-in, personalised checks. Your own history can tilt what you see. Use a clean session.
• Counting only links. A brand can be named without a link, and linked without being named.
• Branded queries only. Your name in the query guarantees you appear. Use unbranded buyer questions.
• Mixing AI Overviews and AI Mode. Google notes the two may use different models and techniques, so their links vary. Record which surface you checked.
• Changing the query list. Add queries in a new version, do not edit the old one.

A 30-minute checklist

1. Write 20 unbranded buyer queries and freeze them.
2. Set up a sheet with the five columns from Step 3.
3. Run all 20 in a private window today, then on two more days this week.
4. Tally named brands and cited domains separately.
5. Open the five most-cited pages and note why they were chosen.
6. Run the same 10 queries through one tool and compare it with the sheet.
7. Pick the two queries where a rival is named and you are not, and fix those pages first.

For the wider method, which prompts to track and the guide to getting cited more often cover choosing queries and acting on the gaps.

How we researched this

We reviewed Google Search Central documentation on AI features, the vendors' own product and help pages (Semrush, Ahrefs, thruuu) and Noma's own product facts. We read the top-ranking competitor tool roundup in full. Facts and prices were checked on 2026-10-31. We did not run hands-on tests of the third-party tools, and the worked example above is illustrative arithmetic, not measured data.

What to do next

Run the manual checklist this week and keep the sheet. If you want the same view across 13 AI engines, daily, without the copy-paste, book a demo or start the free trial.