Fact-Checking
Fact-checking is the systematic verification of statements, figures and claims for their accuracy against reliable sources. In the context of AI visibility this means: you make sure that all information on your website is correct, current and verifiable. That way your content becomes trustworthy and citable for AI assistants.
Why fact-checking matters for AI visibility
AI assistants like ChatGPT, Perplexity or Google AI Overviews look for content they can trust. Wrong figures, outdated opening hours or contradictory information lower the likelihood that a language model names your page as a source. Models judge reliability using signals such as consistency across pages, agreement with other sources and clear evidence. When your facts are correct and remain stable, your citability rises. In addition, clean fact-checking protects against so-called hallucinations: when an AI draws its own conclusions from vague or wrong information, invented statements about your company arise. Correct, unambiguous facts leave the model less room for such errors and strengthen your brand.
How fact-checking works in practice
Fact-checking proceeds in clear steps. First you collect all verifiable statements on a page: prices, figures, dates, names, awards, quotes. Then you check each one against a reliable primary source, for example internal systems, official registers or manufacturer specifications. For statistical statements you go back to the original study, not to a second-hand summary. Then you document the source so that the check remains traceable. Finally, you determine when the information will be checked again, because facts age. A simple editorial rhythm, for example quarterly, keeps your content current. Separation is important: opinions and forecasts are not facts and should be marked as such.
Common mistakes in fact-checking
The most common mistake is relying on secondary sources. If three blogs copy the same figure, that does not make it correct; often it goes back to a single error. A second mistake is a lack of currency: information is correct at the time of publication but becomes outdated unnoticed. Equally risky are contradictory facts on different subpages, because AI models recognize such inconsistencies and downgrade the source. Confusing rounded estimates with exact figures also leads to problems. Finally, many underestimate the duty to provide evidence: a claim without a visible source appears weaker than one with a clear origin. Anyone who avoids these mistakes builds measurably more trust.
Relation to E-E-A-T and AI recommendations
Fact-checking is a core building block of E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness), the quality framework by which search engines and increasingly AI systems measure content. Trustworthiness does not arise through assertion but through demonstrable accuracy. When an AI assistant decides which source to recommend in an answer, perceived reliability plays a large role. Checked, current and sourced facts significantly increase your chance of an AI recommendation. So combine fact-checking with clear author profiles, visible update dates and source references. This combination signals to both human readers and language models that your content is robust, the basic prerequisite for being cited at all.
Example
An online shop for bicycles writes on a guide page: "E-bikes have a legal top speed of 25 km/h." Before publication, the editorial team does not check this statement in another blog but in the official regulation. It confirms: for pedelecs, motor support does indeed end at 25 km/h. In addition, the shop links to the legal source and notes the check date. When, six months later, a reader asks an AI about e-bike rules, the model draws on this documented, current page as a trustworthy source, instead of an unverified forum post.
Common questions
How often should I check facts on my website?
Critical information such as prices, opening hours or legal values you should check immediately with every change, and otherwise at least quarterly. Static facts such as founding years are fine once a year. What matters is a fixed rhythm so that nothing becomes outdated unnoticed.
Can AI assistants really tell whether my facts are correct?
AI models do not check absolute truth, but they assess signals: do your details agree with other sources, are they internally consistent and backed by evidence? Consistent, well-sourced facts increase your citability and lower the risk of hallucinations about your brand.