Freshness and named authorship are the same kind of trust signal to an AI engine that they are to a careful human reader: a dated, attributed page reads as maintained and accountable, while an undated, anonymous one reads as a higher risk to cite. Both signals are cheap to add and directly increase how confidently a model will quote your content.
Why it matters for AEO. AI engines weigh recency and demonstrated expertise similarly to how Google's E-E-A-T (Experience, Expertise, Authoritativeness, Trust) guidelines work - an unattributed, undated page reads as lower-confidence than a dated one with a named author.
How to do it
- Add a visible "last updated" date to evergreen guides and comparison pages, and actually update them on that cadence.
- Attribute articles to a real named author with a short bio, ideally with an Author schema or sameAs link to their LinkedIn.
- Cite your own primary data or research where you have it - usage stats, survey results - since original research is exactly the kind of source LLMs like to attribute.
- Fix or remove outdated claims, such as old pricing or deprecated features, the moment they go stale, rather than letting content quietly rot while new pages are written.
How to verify. Spot-check your 10 highest-traffic pages: each should have a visible date and, where relevant, a named author byline.
Example
"Updated July 2026 by Jane Doe, Head of Growth"
# placed directly under the H1 of a guide, linked to a
# short author bio.