Google AI Mode cited LinkedIn in 31.19% of its sourced answers to our B2B marketing questions in October 2026, and ChatGPT cited it in 0.1%.1 A sourced answer cites at least one page. A LinkedIn plan built on one number for all of AI search is planning for an engine that does not exist.
This page is for B2B software marketing teams deciding how much LinkedIn work AI search can justify, and the answer starts with which engine and which question.
Empact Partners is a consultancy that has worked on go-to-market inside B2B software companies since 2020, and getting partners named in AI answers is part of it. Our Empact Panel asks AI engines fixed questions weekly and keeps every source cited. These are its 4,200 answers to 500 questions about B2B marketing services, 4 to 23 October: the category we sell in, and no benchmark for software buyers.1
Highlights
Add them up and the case for an executive posting schedule gets thin. ChatGPT mostly left. Google AI Mode stayed, on some questions and not on others, and what it cites on questions like ours is a short stack of ranked lists. The number worth having is the one for your own questions, and nobody has published it.
ChatGPT Nearly Stopped Citing LinkedIn After The Quoted Studies Closed
Two studies supply the LinkedIn numbers you are most likely to be handed, and both windows closed in February. Semrush, working with LinkedIn, read 325,000 prompts across 12 industries in January and February and published on 10 March:
Profound’s window closed on 15 February, and it published on 9 March:
Both studies measure their months well. Neither reached the spring, which is when ChatGPT’s line breaks.
Our sister company Qvery builds AI agents that measure brand visibility. Its GEO Agent records what ChatGPT and Google AI Mode say, every day, to the buyer questions it follows, about 749,000 answers by September.6 We own it, so discount it accordingly and check the evidence: its LinkedIn statistics print the series and the method.
On questions that lean to software, services, insurance, and travel:
Qvery can give the date and cannot give the reason.
ChatGPT was citing less of everything that spring: seoClarity measured its citation volumes down 86% to 94% from February to April across five markets.8 That is only part of it. On the day LinkedIn fell hardest, Qvery’s answers carried more links than the days before.3
cloro, a monitoring company using its own prompts, is the independent check:
So ChatGPT nearly stopped, and in cloro’s numbers it has been climbing since August from a very low base.
You will meet a rising number too. Otterly has LinkedIn’s share of social citations going from 7.8% to 11.7% between January and May, across six engines, with 43.3% from Perplexity.9 It also counted 245,352 citations on ChatGPT over those five months, a total that spans the fall. Neither is a rate on ChatGPT after March.
Set the readings by date and most of the disagreement goes away.
| Who measured, and when | ChatGPT | Google AI Mode |
|---|---|---|
| Semrush, 12 industries, Jan to Feb 20262 | 14.3% | 13.5% |
| Qvery, tracked buyer questions, Jan 20263 | 14.67% | 7.57% |
| Qvery, same questions, Apr 20263 | 0.28% | 14.61% |
| Qvery, same questions, Jul 20263 | 0.21% | 11.86% |
| cloro, commercial prompts, 30 days to 7 Aug7 | 0.57% | 6.2% |
| Qvery, ten industries, Sep 20263 | 0.65% | 1.20% |
| cloro, commercial prompts, 30 days to 12 Oct7 | 1.8% | 1.96% |
| Empact Panel, B2B marketing services, 4 to 23 Oct 20261 | 0.1% | 31.19% |
Semrush and cloro divide by all answers, and Qvery and our panel by sourced answers, a gap of under a point on our own numbers. ChatGPT’s column is the finding. Every reading after March sits under 2%, on three instruments and very different questions, against about 14% before it.
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Empact Partners works on the pages AI engines read until a partner gets named on them, which is our Generative Engine Optimization work. It starts by measuring each engine on its own, because a blended number would have hidden that whole column.
LinkedIn Has Passed Reddit Only On Some Engines And Questions
That column also settles half of the argument over whether LinkedIn has overtaken Reddit. On our questions, in October:
Reddit leads LinkedIn on both engines that cite it, on these totals.
Both totals lean on one question group. On ChatGPT, Reddit sits at 74.92% on Reddit-marketing questions and 0.82% to 1.53% on every other group, so it cites Reddit when the question is about Reddit.1 On Google AI Mode those questions lift Reddit to 63.42%, against 38.66% on AI visibility, 17.62% on SaaS go-to-market, and 16.63% on content and SEO.1
Set our Reddit-marketing questions aside and LinkedIn leads on Google AI Mode, 33.21% against 29.75%.1 Outside our category the order moves again:
So LinkedIn has passed Reddit on some B2B questions in Google AI Mode and on nothing we can read in ChatGPT. Anyone saying “overtaken” without naming the engine and the questions is giving you half a sentence.
The Question Sets Google AI Mode’s LinkedIn Rate
Reddit’s swing by question group has a LinkedIn twin. Google AI Mode’s LinkedIn rate inside our one category, over one month:
The overall rate held at 28.11% to 33.87% across the four runs, so one odd week does not explain it.1 Each question ran four times, and 216 of the 500 questions drew LinkedIn in no run at all.
Qvery’s questions show the same thing across a wider range of subjects:
Its September research, on buyer questions in ten industries, found LinkedIn in 0.65% of ChatGPT’s and 1.20% of Google AI Mode’s sourced answers.3 cloro had Google AI Mode at 6.2% in August and 1.96% in October, after the engine cut its links from about 14 sources to about 5 in a cited answer, for every domain.7
cloro’s prompts lean to retail, travel, consumer goods, and software, and it says itself that B2B questions would very likely place LinkedIn higher. So Google AI Mode’s LinkedIn rate runs from about 1% to about 31% in the same autumn, depending on whose questions get asked. No published average can set your budget, and that includes our 31.19%.
That sorting is where a partnership with us begins. Our audit reads what each engine cites on a partner’s buyer questions, and the roadmap comes from that rather than from a content calendar. A named senior consultant owns it, standing reports read each engine separately with a first step on every recommendation, and momentum is usually months out.
On Questions Asking For A Pick, LinkedIn Mostly Means A List Article
Sorting the questions shows where LinkedIn appears. The address shows what appeared, because the first word after linkedin.com names the page type. Google AI Mode’s 687 LinkedIn citations on our questions were overwhelmingly articles, and a posting schedule produces almost none of what it read.1
Those 687 citations point to 115 distinct addresses, shared very unevenly.1
Reading all 115 by hand explains it. 42 of the 50 articles were lists, each ranking or counting companies or tools, and 86.46% of LinkedIn’s citations went to lists.1 Set those aside and the 31.19% shrinks to 3.5% of sourced answers. And the answers lean on LinkedIn when they cite it: 41.34% of the citations sit first in the answer’s sources.1
Our panel is built on buying questions: 472 of 500 questions ask for a pick.1 Qvery’s list study put 76.91% of sourced answers on Google AI Mode at one list or more in July.11 Our read is that an engine asked to choose reaches for a page that has already chosen, and anyone can publish one on LinkedIn, a domain it already reads.
Other instruments read the mix differently, and their questions differ too. Semrush reported its split as a band across three engines.2
Those run from mostly articles to mostly posts, and our panel cannot referee, because only 28 of our questions do not ask for a pick. Our read, and only that: buying questions pull lists and work questions pull people’s writing. If your buyers ask “which tool”, expect our mix. If they ask “how do we fix this”, expect Qvery’s.
People Beat Company Pages In Some Counts And Not Others
A posting schedule usually arrives with a second instruction, to post from personal profiles because company pages do not get cited. The counts behind it do not agree on what they count:
The rule holds on two engines, flips on a third, and changes with what gets counted. On our questions it barely applies, since the article carries the citation whoever signs it, and 2 of the 8 most-cited lists came from a company’s own account.4
People also quote a shift from profiles to posts. Profound measured it on ChatGPT in the three months before the fall.5
That mix describes the LinkedIn citations ChatGPT had in February, and on Qvery’s record it had far fewer of them by April.
Cadence And Engagement Describe Pages Already Cited
The posting advice leans on Semrush’s profile of cited posts and authors:
Every line describes people who were cited. None counts the people who post five times a month and never get cited, so none can tell you what a schedule buys.
Otterly found likes and comments correlate near zero with citations, and says plainly that its data holds only already-cited addresses.9 Qvery found the median cited post was about six months old.3 Our panel tracked whether an address came back across four runs: 27 of 32 posts appeared in one run and 5 in two, while 10 of 50 articles appeared in all four.1
The Company That Publishes The List Gets Named Far More Often
Who wrote the cited pages is the next question. We read the eight most-cited lists on LinkedIn, which took 76.42% of the citations.4
5 of the 8 put their own publisher first, by the page’s own disclosure or because it came from that company’s account, and those five carry 55.17% of LinkedIn’s citations.4 The other three do not say, so we did not count them. The most-cited list says so in plain words, which deserves credit.
Whether it pays can be tested, because each question ran four times and the same question sometimes cites a list and sometimes does not. The most-cited list’s own company was named in 39.54% of the answers citing it, and in 7.14% of sourced answers to the same questions that did not.4 Pooled across the lists:
| Who gets named | Answers citing the list | Same questions, not citing it |
|---|---|---|
| The publisher’s own company, first on its list4 | 41.05% | 6.32% |
| Other companies on the list4 | 28.12% | 15.85% |
| Tracked companies not on the list4 | 1.33% | 1.56% |
Companies absent from the list are named no more often when the answer cites it, so answers citing a list do not simply name more of everyone. The publishers’ own rates run from 2.94% to 73.91% across the four lists whose company our panel tracks, so the pooled figure hides a wide spread.4
In our October answers, a company that ranked itself first on a LinkedIn list was named more often when the answer cited that list. This comparison cannot prove cause. An answer may take the name from another page and cite the list as well, or reach the list because it already had the name.
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We sell this work, and our own number is unflattering: Empact Partners was named in 1 of 4,200 answers to questions in our own category.1 We have no LinkedIn result of our own to show, and none of our partners has published one, so we cannot vouch for a method here.
What we do run is Existing Article Outreach, which gets a partner named on lists an engine already cites. It works on pages the engine reads today. If your buyers’ engine reads a list that leaves you out, that is where we would start.
What These Numbers Cannot Settle
Nothing on this page connects a LinkedIn citation to pipeline, in our numbers or in anyone’s. A citation is a link under an answer, a named company is closer to a recommendation, and neither is a booked call.
Our panel covers one category and one month. LinkedIn’s rate may run high here because the companies publishing answers to these buying questions also sell the services being recommended. We do not measure the other engines either. In cloro’s October corpus, the share of answers citing LinkedIn was:
Two things could make this page wrong by spring: ChatGPT’s rebound could keep going, and Google could stop reading lists that companies wrote about themselves. We would not build a year’s plan on either staying still.
Our verdict is that a LinkedIn posting schedule should not get funded on the strength of AI search until someone has read what that engine cites on the team’s own questions. LinkedIn may still earn the budget for reaching people, which is a different case with a different number.
If LinkedIn is in your AI search plan and you want to know which of your buyers’ questions it can reach, book a call with me, so we can find out whether we could work together.
Sources
- Empact Partners, Empact Panel, our own category: 500 questions about B2B marketing services and AI visibility, each asked four times on ChatGPT and Google AI Mode, 50 of them also on Claude; 4,200 answers collected 4, 9, 16, and 23 October 2026 (Bright Data on 4 October, DataForSEO after that). Sourced answers cite at least one page. Read 30 October 2026.
- Semrush, We Analyzed 89K LinkedIn URLs Cited in AI Search: Here’s What Drives Visibility, 2026; 325,000 prompts across 12 industries on ChatGPT Search, Google AI Mode, and Perplexity, January to February 2026, with LinkedIn.
- Qvery, LinkedIn AI Citation Statistics: Google AI Mode Cites People’s Posts on Work Questions, 2026; the GEO Agent’s daily records, December 2025 to July 2026, and research across ten industries, September 2026.
- Empact Partners, our reading of the eight LinkedIn list articles Google AI Mode cited most in that panel, on the public pages, 30 October 2026, and the comparison of named companies against the panel’s 165 tracked entities, 4 to 23 October 2026.
- Profound, LinkedIn is the most-cited domain for professional queries in AI search, 2026; real ChatGPT prompts and a synthetic professional prompt basket, 15 November 2025 to 15 February 2026.
- Qvery, the GEO Agent’s records: ChatGPT answers since 28 October 2025 and Google AI Mode answers since 18 December 2025, about 749,000 answers, read 19 September 2026.
- cloro, LinkedIn Articles vs Posts: AI Citations Fell 65%, 2026; a fixed 116-prompt cohort, February to July 2026, and six engines in the 30 days to 7 August and to 12 October 2026.
- seoClarity, Tracking the Decline of ChatGPT’s Citations: A Global Trend Analysis, 2026; US, UK, Canada, Germany, and Italy, February to April 2026.
- Otterly, LinkedIn AI Search Citations Study, 2026; 1,310,455 LinkedIn citations on six platforms, 1 January to 1 June 2026.
- Meltwater, 9.5M AI citations analyzed: How LinkedIn content wins AI search, 2026; thousands of B2B prompts on six platforms, four weeks, with LinkedIn.
- Qvery, Are Listicles Still the Most Cited Pages in AI Search?, 2026; the GEO Agent’s records, July 2026.
