Become the source AI cites
Be the verified reference that ChatGPT, Claude, Gemini and Perplexity read from, instead of being paraphrased, outdated or skipped in favor of a competitor.
Reference · 2025–2026 data
Why a company needs a Wikipedia page: search, AI answers, trust
800 million people ask ChatGPT every week, and 2 billion a month see Google's AI answers. Assistants build an answer from a handful of trusted sources: Wikipedia, Wikidata, Reddit, independent media. Your website is just one source, and not the weightiest.
// every number is sourced at the bottom of the page · audit 3–5 days · the result is a probability, not a guarantee
What is known about Company N?
×Wikipedia×Wikidata×media×Reddit
- CChatGPTsources: 0
There is little reliable data on Company N. It seems to be a small company; I can't say more precisely.
- GGeminisources: 0
Company N was founded, probably in 2018. I found no other details.
- PPerplexitysources: 0
Known players in this niche are Competitor X and Competitor Y. I found no mentions of Company N.
- AAI Overviewssources: 0
Top providers: Competitor X, Competitor Y, Competitor Z.
sources: 0facts matched: 0/4
What is known about Company N?
✓Wikipedia✓Wikidata✓media✓Reddit
- CChatGPTsources: 2
Company N was founded in 2011, headquartered in Warsaw [1][2].
- GGeminisources: 2
The company is led by the CEO named in its Wikidata entry; its main product is industrial sensors [2][3].
- PPerplexitysources: 3
Company N, 2011, Warsaw: an industrial sensor manufacturer. Mentioned in independent media [1][3][4].
- AAI Overviewssources: 3
An industrial sensor manufacturer founded in 2011, headquartered in Warsaw [1][2][4].
sources: 4facts matched: 4/4
without sources
with sources
Your brandSources AI trustsAssistantsBuyer
3.4×more often GPT-3 saw Wikipedia than the ordinary web
№1source of ChatGPT citations (Ahrefs, 2025)
1%of clicks go to a link in an AI answer (Pew, 2025)
93%of our pages pass review
01Three layers
How AI assistants build an answer about a brand: training, retrieval, entity
Three layers, and in each of them Wikipedia or Wikidata is among the default sources.
1
Training layer
Every model with a published training mix oversamples Wikipedia. GPT-3 gave it ≈3% of the mix but showed it for 3.4 epochs: more than any other source. The entire open web got less than one epoch. In Meta's LLaMA, Wikipedia's share is 4.5%.
2
Retrieval layer
ChatGPT with browsing, Perplexity, Gemini and AI Overviews pull from the live web. They reach first for the same set: Wikipedia, Wikidata, Reddit, Quora, independent media.
3
auto
Entity layer
Behind a confident answer stands an entity, usually a Q-id in Wikidata. With one, AI sees a known company with verified facts. Without one, a brand is just a string of letters to the model.
Query
Model
Live web
Entity
Wikipedia
Wikidata
Reddit · Quora
Media
Answer
Sources: GPT-3 ("Language Models are Few-Shot Learners", OpenAI, May 2020, Table 2.2); LLaMA (Meta AI, February 2023, Table 1). The composition of closed models is not published.
Assistants with search answer from live sources. How often and which ones they cite is covered in the "Evidence" section.
A Q-id is a company's record in Wikidata: name, founding date, leader, website. The knowledge panel is assembled from it.
02Evidence
Wikipedia in AI answers by the numbers: three independent studies
Different methods give different leaders, but Wikipedia and Reddit consistently sit in the top two.
GPT-3 training
ChatGPT citations
Who is #1
auto
GPT-3: how many times the model saw a source training epochs
Wikipedia3.4×
WebText22.9×
Books11.9×
Common Crawl entire web0.44×
Books20.43×
Source: GPT-3 paper (OpenAI, May 2020), Table 2.2. Values are training epochs: how many times the model saw a dataset. Wikipedia is ≈3% of the mix but has the most repeats. The composition of GPT-4, Claude and Gemini is not published.
Share of citations in ChatGPT illustrative
Wikipedia~13%
Reddit~12%
OpenAI~6%
Walmart~3%
YouTube~3%
Source: Similarweb, ~600K ChatGPT citations, January–February 2026. A vendor study: shares depend on method and month, so the figures are illustrative.
Where the source ranks among the most cited different methods
ChatGPTPerplexityGeminiAI Overviews
Wikipedia✓yes✓yes✓yes✓yes
Reddit✓yes✓yes✓yes✓yes
Quora✓yes✓yes—no✓yes
Wikidata, knowledge graph✓yes—no✓yes✓yes
Tier-1 media✓yes✓yes✓yes✓yes
Ahrefs Brand Radar, 78.6M queries, June 2025: Wikipedia is #1 in ChatGPT (16.3%) and AI Overviews (8.4%), #2 in Perplexity (12.5%). Profound, 680M citations, 2025: Reddit is #1 in AI Overviews and Perplexity. The methods differ, so the leaders differ. The Quora, Wikidata and media marks come from open citation studies.
03Zero-click search
Search with an AI answer: the source matters more than the ranking
When Google shows an AI answer, sites get clicked half as often. The winner is not who ranks #1 but who is named in the answer.
AI answer
Sensors for a small factory are chosen on accuracy, price and warranty. Suppliers are compared using independent reviews and encyclopedic descriptions.
Wikipedia: Industrial sensorsSupplier A: industrial sensorssupplier-a.example
Supplier B: catalog and pricessupplier-b.example
Review: how to choose a sensorreview.example
Supplier C: terms and warrantysupplier-c.example
Without an AI answer
With an AI answer
Click in the answer
15of 100
click on any site when there is no AI answer
8of 100
click on any site when an AI answer sits above the results
1of 100
click a link inside the AI answer itself
Pew Research Center, 68,879 Google searches, July 2025: a click on any site is 15% without an AI answer and 8% with one; on a link inside the answer, 1%.
Bain & Company, February 2025: ~60% of searches end without a click. In February 2024 Gartner forecast a 25% drop in classic search volume by 2026; that is a forecast, not a measurement.
04Wikidata
Wikidata and the Google knowledge panel: an entity, not a string of letters
Wikipedia, Wikidata and Commons are public sources of Google's knowledge graph. We do not guarantee a knowledge panel: Google builds it.
Wikipediaarticle: history and context
Wikidatastructured facts
Wikimedia Commonsimages and files
Google Knowledge Graphentity of Company N
Company N
Technology companyAn industrial sensor manufacturer. source: Wikipedia
- Founded
- 2011Wikidata
- Headquarters
- WarsawWikidata
- CEO
- First LastWikidata
- Website
- n-company.exampleWikidata
- Social media
- 3 profilesWikidata
06Authority and reach
342 Wikipedia language editions: where a page carries the most weight
66 million articles, 508 million views a day (Pew, 01.2026). English Wikipedia has a DR of 96 and ~45M keywords (Ahrefs, 03.2026).
160+ editions we have worked inDomain Rating, 0–100
- Englishen.wikipedia.org94
- Germande.wikipedia.org91
- Frenchfr.wikipedia.org91
- Spanishes.wikipedia.org91
- Portuguesept.wikipedia.org89
- Chinesezh.wikipedia.org89
- Arabicar.wikipedia.org88
- Ukrainianuk.wikipedia.org88
Domain Rating (Ahrefs, 0–100): reference values from our dataset, checked in June 2026, margin of error ±2 points. For English, Ahrefs showed 96 in March 2026: values drift between index updates.
07What a page gives
A Wikipedia page for business: six outcomes and three cases where it is not worth it
One asset that works in search, AI answers, the press and negotiations. But not for every company.
Trigger the knowledge panel
Wikipedia and Wikidata are the strongest signals for the card on the right that shapes the first impression of a brand name. No guarantee: Google builds the panel.
Hold page one for your brand
Wikipedia has a DR of 96 and ranks for ~45M keywords (Ahrefs, 03.2026). A page gives stable visibility with no ad spend.
Pass due diligence
Journalists, analysts, partners and investors check Wikipedia first. A neutral, well-sourced page often settles it: "this company is real."
Reach new markets
160+ language editions we have worked in: local trust where you sell. Each edition is a separate source that AI reads.
An asset that compounds
Built once and maintained, a presence on Wikipedia and Wikidata keeps returning trust and visibility for years, in channels that did not exist when you started.
When a page will not help or will hurt
Early-stage startup with no independent coverage
Nothing to build on: Wikipedia accepts only what independent sources confirm.
Mostly negative coverage
An article reflects what independent sources write, criticism included. It cannot be removed.
Regulated industry with court cases
Court cases and regulator rulings, if independent sources report them, will also end up in the article.
In these cases we start with Wikidata, independent media or Wikitia. Wikitia page creation →
08DIY, freelancer, agency
Writing a Wikipedia page yourself: risks and a comparison of four routes
Writing about yourself is not forbidden but is discouraged: conflict of interest, disclosure, review. One bad attempt stays in the history.
Notability, reliable sources, neutral point of view, conflict of interest: Wikipedia is an encyclopedia, not a marketing channel. A promotional tone gets flagged or deleted.
If it turns out that employees wrote the page, it can be flagged or deleted, and editors' trust is hard to win back.
Deleted attempts leave a trace in the article's history and make the next creation harder. A cheap, inexperienced contractor is the route by which brands lose editors' trust.
What is needed
DIYby your own team
Freelancerfrom a marketplace
Agencyno specialization
WikiBusines93% pass review
Notability assessment before payment
✕no✕noSometimes✓yesEncyclopedic text without conflict-of-interest risk
✕noRiskRisk✓yesWikidata entity
✕no✕no✕no✓yesReddit and Quora for AI visibility
✕no✕noRarely✓yesMonitoring and defending the page after publication
✕no✕noSometimes✓yes80% refund if a published page cannot be defended after 3 attempts within the 90-day window
✕no✕no✕no80%The "DIY", "Freelancer" and "Agency" columns are our assessment from project experience, not a measurement. 93% of the pages we create pass Wikipedia's review and are published (WikiBusines data).
What we promise and what we do not
- We do
We tell you when your source base can support a page and when it cannot.
- We do
We build a reliable, neutral, verified presence on Wikipedia, Wikidata, Reddit and Quora. Paid editing is disclosed on Wikipedia in WikiBusines' name.
- We do
We refund 80% of the fee if a published page cannot be defended after 3 attempts within the 90-day window.
- We do not
We do not guarantee publication on Wikipedia: it is an independent community with its own editorial review.
- We do not
We do not promise a Google knowledge panel: the decision belongs to Google's systems, and we materially raise the probability.
- We do not
We do not insert content into ChatGPT or any other model: we build the sources that AI reads.
09Questions and answers
Wikipedia and AI: frequently asked questions
Why does Wikipedia matter for AI, not just for Google?
AI assistants answer not only from your website but from a small set of trusted sources. Wikipedia is the most-read of them: models weight it most heavily in training, and it is among the most-cited domains in AI answers. Without a presence there, AI guesses about your company or retells your competitors.
How much does it cost and how long does it take?
A company page on English Wikipedia costs €2,400 (a person, €1,620); other languages cost less. Creation takes 4–5 weeks: brief, draft, review, account preparation, publication. Then 90 days of monitoring and guarantee. We assess notability first: if there are not enough sources, we will say so honestly.
What if it is too early for English Wikipedia?
Often the realistic routes are a Wikidata entry, Simple English Wikipedia or another language edition with a lower threshold. They build a presence in the Wikipedia ecosystem and signals for the knowledge graph and AI while you build media coverage for English.
How is AI visibility different from SEO?
SEO optimizes a page you control. AI visibility builds the base of sources AI systems read about you: Wikipedia, Wikidata, Reddit threads, Quora answers, independent media. It is editorial work on sources, not technical work. About AI visibility →
Do you guarantee my brand will appear in ChatGPT answers?
No. Model providers control both training and retrieval themselves. We build sources that raise the probability and track how AI systems describe the brand over time. What they say today is shown by the €490 AI audit, 3–5 days.
Can you get a knowledge panel without a Wikipedia page?
Sometimes. A well-filled Wikidata entry, steady independent coverage and clean schema markup on your own properties can produce a panel for a sufficiently well-known subject. But Wikipedia remains the strongest signal, and panels without it are thinner and less stable. If a page is off the table right now, we start with Wikidata and sources and say honestly what that will achieve.
Sources and methodology
Citation shares depend on the method and change; we update them every year. Dates follow the study's publication.
- OpenAI / Brown et al. — Language Models are Few-Shot Learners (GPT-3), Table 2.2 (May 2020)
- Meta AI / Touvron et al. — LLaMA: Open and Efficient Foundation Language Models, Table 1 (February 2023)
- Ahrefs Brand Radar — Top 10 Most Cited Domains by AI Assistants (78.6M queries) (June 2025)
- Profound — AI Platform Citation Patterns (680M citations) (June 2025)
- Similarweb — Most-cited domains in ChatGPT answers (~600K citations) (January–February 2026)
- Pew Research Center — Google users are less likely to click when an AI summary appears (July 2025)
- Pew Research Center — Wikipedia at 25: what the data tells us (January 2026)
- Wikimedia Foundation — New user trends on Wikipedia (October 2025)
- Bain & Company — Consumer reliance on AI search results (February 2025)
- Aggarwal et al., Princeton / KDD 2024 — GEO: Generative Engine Optimization (GEO-bench, 10,000 queries) (November 2023)
- CBS News / Reuters — Google to pay Reddit ~$60M/year to train AI on its content (February 2024)
- Amsive — Reddit's explosive SEO growth (Sistrix / Ahrefs data) (May 2024)
- OpenAI (Sam Altman) via TechCrunch — ChatGPT has hit 800M weekly active users (October 2025)
- Alphabet Q2 2025 (Sundar Pichai) via TechCrunch — Google's AI Overviews have 2B monthly users (July 2025)
- Gartner — Gartner predicts search engine volume will drop 25% by 2026 (February 2024)
- Ahrefs — Wikipedia Domain Rating & keyword footprint (March 2026)
AI visibility audit: what assistants say about you today
Send us your company name and website. In 3–5 days we will show the answers of ChatGPT, Gemini, Perplexity and AI Overviews, their sources and a 90-day plan.
- 1Company name and websiteHow buyers search for you.
- 22–3 competitorsWho you are compared with.
- 3What worries youAI does not know you, mixes up facts or recommends a competitor.
05Discussions
Reddit and Quora in AI answers: why assistants cite discussions
Google pays for Reddit data, and Perplexity and AI Overviews cite it most often. Quora is a library of buyer questions that AI reads the same way.
What Google reportedly pays Reddit for a license to its content.
CBS News / Reuters, February 2024Reddit's climb among the most visible domains in Google search: in under a year.
Sistrix via Amsive, 2024The most-cited domain in Google AI Overviews and Perplexity by Profound's method.
Profound, 680M citations, 2025Quora works like Reddit but in a different format: the "question → answer" pattern matches a query to AI, so assistants read it the same way. This page has no separate numbers for Quora because there is no reliable source.
A sensor supplier for a small factory: who would you recommend?
Compare price and warranty, not just the brand. Read what independent reviews say.
How do you choose an industrial sensor supplier?
Check whether independent sources exist about the company, and compare the warranty terms.
Reddit for AI visibility →Quora →