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How concentrated are AI recommendations by industry?

How concentrated are AI recommendations by industry?

Published Jul 8, 2026Updated Oct 12, 2026

On this page
  • The finding
  • How we measured
  • Sources
  • More like this
  • The finding
  • How we measured
  • Sources
  • More like this

Dimitry ApollonskyFounder, Parse

DataWhat reviewed means

Some buyer categories may have a dominant AI recommendation while others offer a broader field of alternatives. We wanted to measure how much the leading brand's share varies between industries.

We analyzed recommendations for 9,658 buyer questions on ChatGPT and Google AI Overviews from October 2025 to April 2026. We compared the leading brand's recommendation weight per question across industries with at least 30 questions, rather than letting the largest categories determine the result.

Some categories have a clear AI favorite; others have room for many brands. The leading brand held a median 81.1% of recommendation weight per question in Consumer Electronics, compared with 22% in Sales and Marketing software.

AI visibility has a category shape

The median buyer question names 11 recommended brands across repeated runs, and the top brand holds 33% of all the recommendations. That average hides the real story: some industries collapse to one winner, while others keep a long list of brands alive.

The industry baseline matters because a 20% share can mean dominance in one market and mediocrity in another.

Most versus least concentrated industries

  • Consumer Electronics81.1%
  • Consumer Goods66.7%
  • Software27.9%
  • Sales and Marketing21.8%
  • 0%50%100%
Median share of all recommendations captured by the top brand in each industry.

Median recommended brands per question
11
Median top-brand share
33%
Buyer questions analyzed
9,658

Takeaway

A useful AI visibility benchmark starts with the category's concentration, not a universal target.

Consumer categories are winner-take-most

Consumer Electronics is the clearest winner-take-most category: median top-brand share is 81.1%, the median question names only three brands, and 84% of questions are decisive, meaning one brand holds at least half of all the recommendations. Consumer Goods, Clothing and Apparel, and Sports follow the same pattern.

Most concentrated industries

Top-brand share (%) · 5 results

  • Consumer Electronics81.1%
  • Consumer Goods66.7%
  • Clothing and Apparel65%
  • Sports62.5%
  • Government and Military53.4%
  • 0%50%100%
Explore the data (5 rows)
Consumer Electronics27481.1384
Consumer Goods34766.7563
Clothing and Apparel11465662
Sports24962.5564
Government and Military4253.4957

B2B software categories keep a long list open

Sales and Marketing sits at the other extreme. The median top brand holds only 21.8% of all the recommendations, the median question names 15 brands, and 73% of questions are open, meaning the leader holds less than 30%. Software, AI, Professional Services, IT, and Data and Analytics cluster around the same open shape.

Most open industries

Top-brand share (%) · 6 results

  • Software27.9%
  • Information Technology25.5%
  • Data and Analytics24.8%
  • Events23.1%
  • Advertising22.3%
  • Sales and Marketing21.8%
  • 0%10%20%30%
Explore the data (6 rows)
Sales and Marketing19121.81573
Advertising4922.31476
Events6223.11571
Data and Analytics23824.81362
Information Technology64325.51361
Software76927.91355

The concentration gap is almost fourfold

The difference between the most and least concentrated industries is about 3.7x on top-brand share: 81.1% in Consumer Electronics versus 21.8% in Sales and Marketing. The median list of brands differs by about 5x: three brands versus fifteen.

Gap in top-brand share
3.7x
Gap in brands named per question
5x
Decisive-question share
84% vs 12%

Consumer Electronics vs Sales and Marketing

The target is the top slot in some industries and a place on the list in others

In winner-take-most categories, the practical target is becoming the one brand AI repeats. In open categories, the practical target is earning a durable slot across a larger list. The same measured share implies a different job.

  • Sales and Marketing15
  • Events15
  • Software13
  • Consumer Goods5
  • Consumer Electronics3
  • 051015
Median recommended brands per question.

The pattern holds on both ChatGPT and Google AI Overviews

The consumer-versus-software gap is not one engine's quirk. Consumer Electronics remains concentrated on both surfaces, with median top-brand share of 88.2% on ChatGPT and 72.7% on Google AI Overviews. Software stays open on both, at 30.6% and 28.0%.

Method check: ChatGPT versus Google

ChatGPT top share (%) · 6 results

  • Consumer Electronics88.2%
  • Consumer Goods77%
  • Financial Services31.4%
  • Software30.6%
  • Information Technology30%
  • Sales and Marketing20.7%
  • 0%50%100%
Explore the data (6 rows)
Consumer Electronics88.272.7
Consumer Goods7754.5
Financial Services31.430.6
Software30.628
Information Technology3026.5
Sales and Marketing20.723.8

The gap survives when every question is run a similar number of times

Some industries have more repeated runs, giving more chances for brand variety. Among questions with 9-13 runs, Consumer Electronics still has a 74.1% top-brand share and four brands; Sales and Marketing has a 19.7% share and sixteen brands.

Method check: questions with 9-13 runs only

Sales and Marketing19.716
Consumer Electronics74.14

The gap survives removing single-brand lookups

Consumer electronics includes some specific product questions. Removing single-brand lookups and keeping only questions where AI named at least three distinct brands still leaves Consumer Electronics at 66.7% top-brand share versus 21.6% for Sales and Marketing.

  • Consumer Electronics66.7%
  • Sales and Marketing21.6%
  • 0%20%40%60%80%
Top-brand share after keeping only questions that named several brands.

This is AI decisiveness, not market share

Top-brand share here is not a market-concentration index. It measures how consistently AI repeats the same recommended brand across runs for a buyer question. That distinction matters: AI can be decisive in a fragmented real-world market, and diffuse in a market with clear offline leaders.

631k
distinct AI brand recommendations in the study

Set goals against your category's baseline

For a Consumer Electronics brand, the question is whether AI repeats you as the answer. For a B2B software brand, the first goal may be earning a stable place in the shortlist.

This is why a universal AI visibility target is misleading. Compare against how concentrated your category is, then decide whether the work is winning the top slot or getting onto the list.

  • AI visibility benchmarks by industry: what good looks like

How we measured

We analyzed 631,087 distinct brand recommendations across 9,658 buyer questions on ChatGPT and Google AI Overviews from October 19, 2025 to April 24, 2026, reporting 38 industries with at least 30 questions.

median top-brand share across all questions
33%
Consumer Electronics median top-brand share
81%
Sales and Marketing median top-brand share
22%
median brands per buyer question
11

Get the data

Dataset CSVIndustry concentration figures and method checks.

Sources

  1. Companion analysis: AI recommendation concentration by industry
  2. Parse public index

More like this

AI recommendation white space: questions no brand owns
Many buyer questions had no consistent first-choice brand, leaving different openings in each industry.
How many brands does AI name in one answer?
Answers naming brands typically included five. Answers naming just one brand were uncommon.
Brands AI recommends on just one engine
Most brands recommended in our matched questions appeared on only one of ChatGPT and Google AI Overviews.
Who owns the brands AI recommends?
About one in five of the most recommended brands belonged to a larger parent company.
Is AI naming fewer brands per answer over time?
Google AI Mode named more brands per answer over the months compared, among answers naming at least one brand.
Where does AI make a clear recommendation?
Reservations varied widely by market. Some categories drew much more qualified recommendations than others.
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.

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