What 860 AI-generated buyer answers across 61 B2B software categories reveal about who gets recommended, who gets ignored, and where AI answers actually get their evidence.
Between July 18 and 23, 2026, Broadcastwell ran 10 standardized buyer questions through AI search with live web results for each of 85 B2B software companies across 61 categories, producing 860 scored answers and 5,160 traceable source citations.
On engines: this study holds one engine constant (Anthropic Claude Sonnet with live web search) across all 860 runs so results stay directly comparable across categories. The full audit runs all four engines — ChatGPT, Perplexity, Claude and Google AI Overviews — and compares them. The single-engine constraint applies to this study only. The four-engine audit method is published in full at github.com/Broadcastwell/audit-method. We also ran that four-engine method on ourselves and published the result, including the part where we scored zero.
One limitation matters up front: all 860 answers came from a single engine, Claude Sonnet with live web search, run once per prompt. This is a snapshot of one system on the days it ran, not a claim about AI search in general. The fuller limitations are in the Methodology section below.
The results describe a market that has quietly re-concentrated. The median B2B company is named in just 20% of AI answers for its own category, and 35% of companies are never named at all. Meanwhile, in most categories a single brand captures 80% or more of all AI mentions. The average answer recommends only 2 vendors: the shortlist has shrunk from ten blue links to two names.
The evidence behind those answers is not what most marketing teams assume. Among the 100 most-cited domains, 77.4% of citations resolve to vendor-authored content, companies writing the category's answer material themselves. Review platforms account for 10.2%, independent media 6.5%, and analyst firms 5.9%. Community sources such as Reddit, Quora and Stack Overflow account for 0.0% of citations among the 100 most-cited domains (1,879 citations, 36% of the total).
The practical implication: in B2B software, AI visibility is not won on community platforms or earned media alone. It is won by publishing the reference content that AI systems retrieve, and by being present on the small set of review platforms they consistently trust.
Across 85 companies, the median company was named in 20% of the 10 buyer answers for its own category. 30 of 85 companies (35%) were named in zero answers. Only 31% of companies were named in at least half.
In each category we identified the single most-mentioned brand across that category's answers. The median category leader appears in 80% of its category's answers. In 50 of 85 company sweeps (59%), the leader appears in 80% or more of answers. In only 3 of 85 does the leading brand appear in fewer than half.
We classified the 100 most-cited domains (1,879 citations, 36% of all citations). 77.4% of those citations resolve to vendor-owned domains: comparison posts, category guides and 'best X software' listicles written by the vendors themselves. Review platforms such as G2, Capterra, TrustRadius and SourceForge account for 10.2%; independent media 6.5%; analyst firms 5.9%, with gartner.com the single most-cited third-party domain in the study (110 citations). Community sources such as Reddit, Quora and Stack Overflow account for 0.0% of citations among the 100 most-cited domains (1,879 citations, 36% of the total).
The 5,160 citations spread across 1,753 unique domains. The top 10 domains account for only 12% of citations, the top 100 for 36%, and 56% of all cited domains appear exactly once. AI answers are assembled from a long tail of category-specific pages, which means visibility is winnable page by page.
'Best X' questions named the measured company 41% of the time; 'X vs Y' comparisons 20%; use-case questions 23%. But in use-case questions, 40% of answers named no vendor at all: unclaimed answer space. Across all 860 answers, 13.1% named zero vendors, and the average answer named just 2.05 vendors (median 2).
Only 47% of answers that named a company also cited that company's own website as a source. And 97 answers cited a company's domain as evidence without ever naming the brand in the recommendation. Naming and citation are separate battles: one is about being retrievable, the other about being the answer.
Volume II extends this work by classifying every absence: The Absence Ladder.
| Segment | Companies | Answers | Avg named | Avg cited | Named in zero answers |
|---|---|---|---|---|---|
| Product & Dev Tools | 21 | 210 | 47.1% | 33.8% | 2 |
| Sales & Marketing Tech | 21 | 220 | 16.7% | 22.4% | 10 |
| Ecommerce & Site Search | 12 | 120 | 18.3% | 15.8% | 5 |
| HR & Operations | 10 | 100 | 26.0% | 24.0% | 4 |
| Customer Experience | 9 | 90 | 28.9% | 22.2% | 4 |
| Data & Analytics | 9 | 90 | 16.7% | 12.2% | 5 |
| Vertical & Niche SaaS | 3 | 30 | 36.7% | 40.0% | 0 |
| All segments | 85 | 860 | 27.5% | 24.0% | 30 |
Average share of a company's ten category answers in which it was named or its domain cited. Vertical & Niche SaaS covers three companies, so treat that row as directional. Sales & Marketing Tech shows 220 answers because one company in that segment was swept twice.
| # | Brand | Mentions | Share |
|---|---|---|---|
| 1 | 6sense | 123 | 14.3% |
| 2 | Demandbase | 101 | 11.7% |
| 3 | Algolia | 63 | 7.3% |
| 4 | Gong | 37 | 4.3% |
| 5 | Bloomreach | 30 | 3.5% |
| 6 | Zendesk | 29 | 3.4% |
| 7 | Terminus | 27 | 3.1% |
| 8 | Constructor | 27 | 3.1% |
| 9 | Clari | 26 | 3.0% |
| 10 | Freshdesk | 21 | 2.4% |
| Domain | Citations | Type |
|---|---|---|
| gartner.com | 110 | Analyst |
| g2.com | 57 | Reviews |
| peoplemanagingpeople.com | 31 | Media |
| sourceforge.net | 30 | Reviews |
| trustradius.com | 24 | Reviews |
| thedigitalprojectmanager.com | 22 | Media |
| netguru.com | 21 | Media |
| thecmo.com | 21 | Media |
| capterra.com | 20 | Reviews |
Full top-100 domain table available in the dataset downloads below.
Company identities in the underlying sweep data are withheld. Aggregates and brand-level mentions of widely known market leaders are published; per-company results are anonymized.
Broadcastwell Research (2026). The 2026 State of Generative Engine Optimization, v1.0. https://doi.org/10.5281/zenodo.21537014
@report{broadcastwell2026geo,
title = {The 2026 State of Generative Engine Optimization},
author = {{Broadcastwell Research}},
year = {2026},
version = {1.0},
doi = {10.5281/zenodo.21537014},
url = {https://broadcastwell.com/state-of-geo}
}To cite all versions, use 10.5281/zenodo.21537013, which always resolves to the latest.
The median company in this study was named in 20% of its own category's answers. We will run your numbers free: five real buyer questions through ChatGPT and Perplexity, results by email, no call. Want all four engines and a written two-pager? We do that free too.
Run your free check