The new E-E-A-T. Signals AI engines look for in 2026.
Crawlmind Engineering··3 min read
E-E-A-T is Google's framework for judging content quality, standing for Experience, Expertise, Authoritativeness, and Trustworthiness. It started as a guideline for human raters (see Google's creating helpful content guidance) and, over the last decade, filtered into the ranking signal mix. In 2026 the LLM answer engines have adopted a related but materially different version, and the differences are big enough to be worth a focused look.
#What's the same
The fundamentals carry over.
- Real author with a name and a credible track record beats anonymous content
- A site that exists as a registered business with consistent presence across the web beats a free WordPress on a fresh domain
- Citations from authoritative third parties beat self-attestation
- HTTPS, valid certificates, no malware history. The basics.
If you've been doing E-E-A-T well for Google, you're most of the way to doing it well for AI engines.
#What's different
Five places the AI engine version diverges in ways worth knowing.
#1. Author identity is verified across the web, not just on your site
Google could mostly take "author" at face value. AI engines now actively cross-reference. If your "Senior SEO Strategist John Smith" byline has no matching LinkedIn, no X account, no conference talks discoverable through web search, the LLM weighting drops.
Practical action: pick the three or four authors on your site whose bylines you actually care about, and make sure each has a public profile somewhere reputable. A LinkedIn with a real photo and a work history is the minimum.
#2. Recency is now load-bearing
Old E-E-A-T was timeless. A great article from 2018 about cooking techniques is still a great article. AI engines, especially on fast-moving topics, weight recency aggressively. A page about "best CRM in 2024" loses to "best CRM in 2026" even if the 2024 one is better-written.
For evergreen content this is annoying. For SaaS marketing it's existential. Quarterly refresh is a strategic requirement, not a nice-to-have.
#3. First-party data beats secondary sourcing
Google rewarded "comprehensive coverage." LLMs reward "this site appears to know things firsthand."
The clearest signal of firsthand knowledge is data the engine can't find anywhere else. An audit of 800 sites. A benchmark you ran. A customer panel you surveyed. If your blog content is just better- written versions of other blog content, the engines notice (because they were trained on the originals).
This is a content-strategy implication: stop writing "ultimate guides" and start publishing small bits of original data. A 600 word post that says "we measured X, here's what we found" outranks a 3000 word post that synthesizes other people's measurements.
#4. Organisational continuity matters
The engines model your domain as an entity over time. A site that publishes regularly under the same brand, with the same authors, with consistent positioning, accumulates trust. A site that rebrands, swaps domains, or stops publishing for six months loses it (and getting it back takes months).
This makes the "let's blog when we have time" pattern especially costly. Better to publish one post a month consistently for two years than 12 posts in a quarter and silence after.
#5. The "publisher" entity is now a thing
Your Organization schema with sameAs links, your LinkedIn
company page with real updates, your Crunchbase / GitHub / X
presence. The engines synthesize these into a publisher entity.
Sites whose publisher entity is robust and consistent get cited at
materially higher rates than sites where the publisher is opaque.
For B2B SaaS this is huge. Your LinkedIn company page being neglected costs you AI citations on your own site.
#A pragmatic E-E-A-T checklist for 2026
A list of 10 things you can audit in an hour:
- Every blog post has a Person author, linked to a real bio page
- Every author bio links to at least one verified external profile
- Every key page has a
dateModifiedwithin the last 6 months - Your Organization schema includes 3+
sameAsentries to real profiles - Your LinkedIn company page is updated at least monthly
- You publish at least one original data point per quarter
- You have a clear, named editor or "owner" listed for the blog
- You haven't changed domains in the last 18 months
- You have a postmortem or changelog visible somewhere (signals "real ops")
- Your contact page lists a real human, not just a form
Score yourself. Most SaaS sites we audit land in the middle of these signals. The ones that score well tend to get cited materially more often.
Related field notes
July 3, 2026 · 5 min
E-E-A-T for AI: authorship, sourcing, dates
The three E-E-A-T signals AI engines can actually parse, and the exact markup and habits that make each one machine-legible.
July 2, 2026 · 5 min
The cost of AI invisibility: a B2B framework
A qualitative way to reason about what your company loses when AI assistants answer buyer questions without ever mentioning you.
July 1, 2026 · 5 min
Canonical and hreflang in an AI-answer world
Canonical and hreflang tags still shape which URL AI engines cite, but they reach the model through Bing's index and get honored unevenly.
Share or discuss
New posts, no spam. Roughly monthly. Unsubscribe with one click.