Data as of Aug 25, 2026 · Based on 351 AI responses · Shares cover the last 30 days · See how Parse measures this
Gartner remains the most-cited source for top-down market sizing, consistently recommended by AI assistants for obtaining high-level industry reports. However, AI responses have increasingly promoted a 'bottom-up' methodology as more defensible, shifting focus to tools like
LinkedIn for customer counting and reframing analyst reports as a validation step rather than the primary source.
Professional Research & Intelligence Platforms
Parse
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| # | Brand | What AI says | Mention rate |
|---|---|---|---|
| 1 | The top-cited source for high-level, top-down market validation and industry reports. | 43% | |
| 2 | Increasingly recommended alongside | 26% | |
| 3 | Consistently cited as a source for traditional, top-down market research reports. | 21% | |
| 4 | A key tool for building more credible, 'bottom-up' market sizing models. | 18% | |
| 5 | Once a top mention, but cited less as focus shifts to methodology. | 18% | |
| 6 | 12% | ||
| 7 | 10% | ||
| 8 | Frequently recommended for foundational firmographic and demographic data for bottom-up analyses. | 9% | |
| 9 | 9% | ||
| 10 | 9% | ||
| 11 | 8% | ||
| 12 | 8% | ||
| 13 | 8% | ||
| 14 | 7% | ||
| 15 | 7% | ||
| 16 | A rising entrant since February 2026, framed as an ultimate guide. | 7% | |
| 17 | 6% | ||
| 18 | 6% | ||
| 19 | 5% | ||
| 20 | Recommended for getting actual customer counts to build bottom-up sizing models. | 5% | |
| 21 | 5% | ||
| 22 | 4% | ||
| 23 | 4% | ||
| 24 | 4% | ||
| 25 | 4% |
Who wins on each AI
The same market, seen by two models.
Sources AI cited
antler.co is the page AI reaches for most here, cited in 45% of analyzed answers.
AI increasingly recommends LinkedIn for credible 'bottom-up' analysis, rising from #10 to #2 in mentions between October and March.
Dropped from rank #1 in October 2025 to #9 by March 2026 as AI answers shifted focus from listing analyst firms to explaining methodology.
First cited in February 2026, it quickly became a top-5 mention, framed as an 'ultimate guide' for the TAM/SAM/SOM process.
| Brand | ChatGPT Search | Google AI Mode | Comparison |
|---|---|---|---|
| 29% | 38% | ||
| 19% | 10% | ||
| 5% | 19% | ||
| 5% | 19% | ||
| 14% | 5% |
Across 351 AI responses, Gartner is mentioned most, named in 43% of them, followed by Statista (26%) and IDC (21%).
Parse measures each brand's mention rate — the share of answers naming it — across 351 AI responses to this market's buyer questions over the last 30 days. Answers are collected daily and the ranking is re-measured on the same 30-day window.
Brands enter the ranking when AI answers mention them. Parse collects answers daily and publishes the re-measured set weekly, so new brands appear as AI starts recommending them.
AI responses have evolved from simply listing analyst firms like Gartner and
Forrester to providing sophisticated methodological advice. Since late 2025, answers consistently champion a 'bottom-up' approach using tools like
LinkedIn as more defensible, while positioning traditional 'top-down' reports as a secondary validation step. This shift increased citations for data sources like the
and new guides like .
Best way to build a defensible TAM/SAM/SOM?
AI responses have evolved from simply listing analyst firms like Gartner and
Forrester to providing sophisticated methodological advice. Since late 2025, answers consistently champion a 'bottom-up' approach using tools like
LinkedIn as more defensible, while positioning traditional 'top-down' reports as a secondary validation step. This shift increased citations for data sources like the and new guides like .