The likelihood that an Answer Engine will reference specific content when generating a response is linked to the content evaluation framework of “Expertise, Experience, Authoritativeness, Trustworthiness” (E-E-A-T). This framework has moved from a Google guideline to the core filter through which AI models decide whose facts are safe to reuse and whose claims never surface.
E-E-A-T is not a traditional SEO guideline, but it is now becoming a crucial filter and a direct input into Answer Engine's decision-making when selecting sources to cite.
Why is this shift happening now?
Google still processes roughly 14 billion searches per day, but the interaction pattern is changing. When an AI Overview appears, clicks drop from 15 percent to 8 percent, and more than a quarter of searches end without any clicks. That’s a structural change, not a design tweak.
The research from a 2025 AEO study shows what that looks like in practice. Answer engines heavily prefer earned media over brand pages, and they reuse those sources across paraphrases, languages, and business verticals. In the smartphone and laptop tests, Google pulled in brand, social, and earned sources in something close to balance, while AI engines leaned as high as 92 percent toward earned outlets.
AI gives weight to Experience, Expertise, Authoritativeness, and Trustworthiness, and it looks for those signals in places where editorial oversight exists. When AI systems synthesize an answer, they need justification. A brand page full of adjectives is harder to cite than a third-party review that lists specs, tests, and drawbacks.
“SEO rewarded framing, AEO rewards evidence.”
E-E-A-T
Expertise, Experience, Authoritativeness, Trustworthiness and how you manage this when creating new content to increase answer engine citations.
Experience: How AI stops generic content
Answer Engines look for verifiable first-hand details: what was tested, how it performed, what went wrong. AI models don’t trust content that reads the same as their own generated text, without any sources. They need signals that the creator touched the subject matter. When this isn’t present, the model downgrades the page’s citation probability.
This is one reason earned media dominates AI citations. Reviewers describe use conditions, calibration tests, defects, and comparisons. AI can quote that. Brand pages often avoid it.
To show experience, content creators must have:
- Clear evidence that the creator has first-hand involvement with the topic.
- Specific, verifiable details that only a person with direct interaction would know.
- Unique photos, walkthroughs, or data showing real use or real insights
- Transparent personal perspective when relevant (what was tried, what happened, what was learned).
Expertise: How AI removes the outliers
Expertise has shifted from a measure of reputation to a measure of consensus. AI models are probabilistic; they predict the next likely word based on their training data. They favor information that aligns with the established consensus inside a specific field.
When asking about cars and other automotive products, Chat GPT cited earned media in more than 80 percent of cases in the United States, with zero social content and minimal brand pages. Google, by contrast, still surfaced social forums and vendor sites .
Content that drifts too far from accepted terminology or facts runs the risk of being treated as an error or a "hallucination."
To show experience, content creators must show:
- Accurate, up-to-date information that aligns with consensus in the relevant field.
- Use of correct terminology and reasoning appropriate for the topic’s complexity.
- Citations to credible sources or original data are provided.
- Content produced by someone with demonstrable training, qualifications, or specialized skill.
Authoritativeness: An AI’s seal of safety
Answer engines Authoritativeness through reputation signals: citations from other sites, clear identity, stable coverage, and recognizability. AI models would rather quote a site with ten years of coverage and public ownership info than a thin affiliate blog repeating specs. This matches the AEO finding that answer engines reuse the same domains across languages and paraphrases, especially in higher-stakes categories. Claude, for example, maintained consistent domain usage across translations where Google did not.
To show Authoritativeness, content creators must have:
- Strong signals of credibility around the creator or the site, such as reputation, recognition, mentions, references, or links from authoritative entities or earned media.
- A clear identity for the creator or organisation with accessible background information.
- Consistent, reliable coverage of the topic area.
Trustworthiness: How AI determines if this is the correct source
AI systems need to avoid reputational harm from hallucinated or untrue claims. To ensure that your content is trustworthy, they rank it based on factors such as Transparent sourcing, Factual accuracy, and Conflict-of-interest disclosures. Together, these create strong signals of a clear editorial process. When those signals are weak, the model may still read the page but exclude it from the output.
Searching for “IT support”, which is defined as a “local business” category, in ChatGPT and then in Google will produce completely different outcomes. This is because site quality varies for local companies, and trust signals are inconsistent. In the test, overlap dropped near zero.
To show Trustworthiness, content creators must have:
- Full transparency about who created the content, why, and how.
- Accurate, non-deceptive claims with verifiable facts.
- Clear sourcing and conflict-of-interest disclosures
- Clear editorial or review processes.
What this means for brands adjusting to AEO
A brand cannot win AI visibility through page-level tuning alone. The shift places pressure on factual clarity, external authority, and machine readability.
Content must state verifiable details that demonstrate genuine experience. Pages must include structured data that enables a model to extract facts without inference. Brands need independent press, comparisons, and reviews that reinforce their authority. Writers must publish clear value claims that can be reused as justification inside an answer. Weak trust signals will get a page silently filtered out.
AI will cite the source that proves it knows what it is talking about, not the one that describes itself best. That’s the competitive field now.
How to check E-E-A-T for free
Audit your content for citability in answer engines. Pick one core product or service and assess whether a model could extract: a first-hand detail, a clear comparison point, a fact with a number attached, and a reason that supports the product’s use case. If any of those pieces are missing, the page is unlikely to appear inside an AI-generated answer for others.
