Name: Single-engine brands in AI visibility
Creator: Parse
Published: 2026-07-08

A brand that appears on one AI engine may be absent from another answering the same buyer question. We wanted to measure how much recommendation coverage the two engines share.

We compared 507,984 clean brand recommendations across 16,206 questions asked on both ChatGPT and Google AI Overviews from October 19, 2025 through April 25, 2026. We excluded a catch-all group that does not represent a real brand before comparing engine coverage.

73.8% of recommended brands appeared on only one engine across 16,206 matched questions in Parse's October 19, 2025–April 25, 2026 sample of ChatGPT and Google AI Overviews answers.

Single-engine visibility is the default state

Across the matched prompt set, meaning the same questions asked on both engines, 49,226 clean brands were recommended by at least one engine. Only 12,914 appeared on both. The other 36,312 appeared on ChatGPT only or Google AI Overviews only.

That makes cross-engine visibility the exception, not the baseline. A brand can look visible in one AI product and still be absent from the other.

Brand visibility class

Google only46.9%
ChatGPT only26.9%
Both engines26.2%
0%20%40%60%

Share of recommended brands by the engine set where they appeared at least once.

73.8%

of AI-recommended brands appeared on only one engine

Takeaway

A blended AI visibility score can hide the main risk: the brand may be winning on one engine and missing on another.

Volume reduces the risk, but it does not remove it

Single-engine exposure falls as recommendation volume rises. Among brands recommended at least five times, 43.8% are still single-engine. Among brands recommended at least ten times, 28.5% are still single-engine. Being established on one engine does not guarantee the other engine.

All recommended brands73.8%
At least 5 recommendations43.8%
At least 10 recommendations28.5%
0%20%40%60%80%

Single-engine share after filtering for brands with more recommendations.

Google AI Overviews casts the wider net

Google AI Overviews issued 384,094 clean brand recommendations in the matched prompt set, versus 123,890 for ChatGPT. That wider net produces more single-engine brands: Google-only brands outnumber ChatGPT-only brands 1.8 to 1 overall, and 7.6 to 1 among brands recommended at least ten times.

Google AI Overviews recommendations: 384k
ChatGPT recommendations: 124k
Google-only vs ChatGPT-only among brands with 10+ recommendations: 7.6:1

The cross-engine minority owns the recommendation volume

Cross-engine brands are only 26.2% of recommended brands, but they capture 71% of recommendations. Single-engine brands are numerous, but most sit in the long tail.

Cross-engine brands26.2% of brands
Cross-engine volume71.0% of recommendations
Single-engine brands73.8% of brands
Single-engine volume29.0% of recommendations
020406080

Share of brands versus share of recommendation volume.

The three brand classes behave differently

We grouped brands into those recommended on both engines, ChatGPT only, or Google only. If you appear on both, compare your position and sources. If you appear on just one, investigate what the other engine recommends and cites.

Brand class by number of recommendations


All brands	49,226	26.2	26.9	46.9	73.8
At least 5 recommendations	19,279	56.2	8.6	35.2	43.8
At least 10 recommendations	10,913	71.5	3.3	25.2	28.5

Single-engine risk depends on the vertical

The risk is highest in consumer, regulated, and long-tail verticals: Manufacturing, Travel and Tourism, Government and Military, Health Care, Professional Services, Real Estate, and Education all sit near or above 50%. Established B2B software categories are lower, but still not safe.

Highest and lowest single-engine risk by vertical

Single-engine (%) · 8 results

Manufacturing56.2%
Travel and Tourism55%
Government and Military54.8%
Health Care52%
Education50.1%
Software40.1%
Sales and Marketing35.5%
Collaboration32.1%
0%20%40%60%

Explore the data (8 rows)


Manufacturing	249	56.2	8.8	47.4
Travel and Tourism	407	55	24.3	30.7
Government and Military	84	54.8	6	48.8
Health Care	711	52	5.9	46.1
Education	787	50.1	3.4	46.6
Software	2,142	40.1	3.9	36.2
Sales and Marketing	622	35.5	6.6	28.9
Collaboration	193	32.1	5.7	26.4

Google-only visibility is the dominant long-tail shape

In nearly every vertical, the single-engine share is dominated by Google-only brands. That does not mean Google is easier to win; it means Google AI Overviews names a wider set of brands, including newer ones and ones that depend more on what its search step pulls in.

Google only
ChatGPT only

Health Care
Google only46.1%
ChatGPT only5.9%
Software
Google only36.2%
ChatGPT only3.9%
0%20%40%60%

Single-engine composition for selected verticals.

ChatGPT-only winners cluster in categories Google avoids

The top ChatGPT-only brands skew toward online casinos and gambling brands, including FanDuel Casino, Raging Bull Casino, SuperSlots, Slots.lv, BitStarz, and Caesars Palace. Those are categories Google AI Overviews rarely surfaces as recommendations.

Top single-engine examples


Google-only pattern	PayPal USD, LlamaParse, Fireworks.ai, Voyage AI, Aave, Varonis
Cross-engine leaders	DraftKings, HubSpot, Rippling, Pipedrive, ClickUp, FanDuel, Notion
ChatGPT-only pattern	FanDuel Casino, Raging Bull Casino, SuperSlots, BitStarz, Caesars Palace

Current HubSpot measurements

Single-engine is not always failure, but it is always diagnostic

A Google-only brand may be newly visible because retrieval found fresh evidence. A ChatGPT-only brand may sit in a category Google avoids. The issue is not that single-engine visibility is bad by itself. The issue is that it tells you where the next measurement and source work should happen.

28.5%

of brands with 10+ recommendations still appear on only one engine

Report AI visibility by engine before blending it

Start an AI visibility report with three groups: brands on both engines, ChatGPT-only brands, and Google-only brands. Show which engine is missing your brand.

Only after that split is visible does a blended score become interpretable. Otherwise the average can hide the most important operational fact: one engine may not know you at all.

Why one AI visibility score is misleading

How we measured

We analyzed 507,984 clean brand recommendations across 16,206 buyer questions run on both ChatGPT and Google AI Overviews from October 19, 2025 to April 25, 2026, after excluding a catch-all group that is not a real brand.

recommended brands appear on one engine only: 73.8%
recommended brands appear on both engines: 26.2%
recommendations captured by cross-engine brands: 71%
Google AI Overviews recommendation volume vs ChatGPT: 3.1x

Get the data

Dataset CSVHeadline brand classes, volume groups, and vertical single-engine risk.

Sources

ChatGPT vs Google: same winner, different shortlist

ChatGPT and Google AI Overviews usually shared the leading brand across buyer categories, but their wider shortlists differed.

How many brands does AI name in one answer?

Answers naming brands typically included five. Answers naming just one brand were uncommon.

How concentrated are AI recommendations by industry?

A few brands dominate consumer electronics recommendations. B2B software recommendations are spread across more brands.

How often does AI recommend against a brand?

AI rarely explicitly advised against a brand for the buyer's stated need in the statements we reviewed.

Do ChatGPT and Google recommend the same top brand?

ChatGPT Search and Google AI Mode chose the same first recommendation in about a third of matched answers.

ChatGPT Search: do answers with sources name the same brands?

Answers with and without recorded sources usually named different first brands in matched comparisons.

Do new brands break into AI recommendations?

Previously named brands kept most first-place picks. Relatively few newly appearing brands reached the top even once.

Does AI localize brand recommendations by country?

Naming a country outside the US often brought a local brand first. Naming the US barely changed the answer.