In early January 2026, another major Google algorithm update was launched, nicknamed the “Authenticity Update” by SEO/GEO professionals and pundits. If you’ve been wondering why you had some major fluctuations in traffic and rankings recently?, this is likely why.
In essence, Google’s ranking systems are getting better at rewarding content that feels human-made and grounded in real, first-hand experience, credible expertise, and verifiable trust signals, while filtering out generic, mass-produced AI pages.
But with Google allegedly getting better at rewarding content by real people over “AI slop,” what does that mean for content creators and marketers?
What happened: a measurable shift toward “human-proof” signals
Around January 6, several industry observers documented volatility but also noted Google had not confirmed a new core update starting that day. Ongoing volatility was also reported later in January.
Where the “Authenticity” framing came from: many SEOs noticed a pattern that resembled an upgrade in Google’s ability to demote pages that read like “AI-shaped filler” and reward pages that demonstrate:
- first-hand experience
- accountable authorship
- unique information gain
- and real-world credibility (citations, reputation, transparency, policies, etc.)
Even if January’s movement remained unconfirmed, it aligns with a direction Google has been telegraphing for a while: scale + low effort + low originality is risky, regardless of whether the content was produced by AI, a human, or both. We’ve also known for years about the importance of E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness), so assuming this is an extension of that makes sense.
Why this is happening now: Google’s incentives in an AI-first SERP
Google is simultaneously dealing with two pressures:
- The internet is being flooded with inexpensive, AI generated content.
Generative AI made it easy to publish thousands of “good-enough” pages quickly. Google’s spam policies and guidance explicitly warn against scaled approaches that aim to manipulate rankings rather than help users. “Scaled content abuse” is the modern umbrella concept here. - Search results increasingly act like answers, not directories.
With AI Overviews, AI Mode, and similar AI search platforms, Google needs high-confidence sources to summarize and cite webpages. That pushes ranking systems (and retrieval systems feeding AI summaries) to prioritize content that’s trustworthy, attributable, and genuinely informed.
This is also why GEO (Generative Engine Optimization, also known as “organic visibility”) is not just SEO with long-tail prompts. In an AI summary world, you’re competing to become the source that gets selected, not merely the result that gets clicked.
What does E-E-A-T really mean in 2026?
As we’ve said, expertise and authority have always been important when it comes to content creation. This extends beyond simply search engine ranking factors, and are keys to reaching your target audience. Google understands this. E-E-A-T is a quality framework used in Search Quality Rater Guidelines and in Google’s own “helpful, reliable, people-first” content guidance. Google is explicit that raters don’t directly set rankings, but their evaluations help Google measure whether algorithm changes are improving results.
In practice, “human-proof” E-E-A-T means your content should carry evidence that a real person (or accountable organization) with legitimate experience and expertise:
- created it
- stands behind it
- can be vetted
- and provides value that’s hard to fake at scale
Google also publishes specific guidance for sites using generative AI: it’s allowed, but content must still meet Search Essentials/spam policies and avoid low-effort, low-originality publishing patterns.
In other words: This isn’t “Google hates AI.” It’s “Google hates unhelpful scale and unverifiable content, and AI makes those problems easier to create.”
What should content creators and organic marketers do moving forward?
1) Design content around information gain, not “coverage”
If your page is interchangeable with 50 others, save for a few geo-focused keywords, it’s vulnerable. Create “information gain” by adding assets others don’t have, such as:
- original examples, screenshots, workflows, checklists you actually use, etc.
- first-party data (even small datasets)
- quotes from practitioners, experts, or even team members that can speak to the subject
- step-by-step decision frameworks
- real pros/cons based on use
A simple test to determine the E-E-A-T of a page: Could a competitor reproduce this page in 15 minutes with a generic AI prompt? If yes, rebuild.
2) Make experience visible (not implied)
“Experience” is the newest “E” and the most commonly missing element in AI-assisted content.
Add proof:
- “What we did” sections (case notes, constraints, timeline)
- photos/screenshots (tools, dashboards, results)
- author anecdotes that demonstrate real contact with the topic
- product/service comparisons done hands-on
3) Upgrade authorship from a byline to an identity
Thin author pages and generic bylines are a missed opportunity.
Instead, do this:
- robust author bio pages (credentials, experience, areas of focus, speaking/publishing)
- editorial policy and review process
- “last reviewed by” where appropriate
- clear contact and business information
You’re not just helping Google; you’re also showing your audience you’re real people.
4) Stop publishing “scaled sameness”
If you’re mass-producing pages that differ only by:
- keyword swaps
- location swaps
- template fluff
- lightly rewritten competitor content
…you’re drifting toward the patterns Google describes under scaled content abuse and “little effort / little originality.”
If you need scale, scale systems, not sameness:
- a strong editorial standard
- unique data inputs
- real expert review
- clear value-add requirements per page
5) Optimize for extractability (GEO-friendly formatting)
Generative systems love content that’s easy to quote accurately.
Make it easy:
- succinct definitions near the top
- labeled steps and decision trees
- FAQ blocks that answer exactly what people ask
- tables where it improves clarity (not padding)
- “Key takeaway” callouts (short and factual)
This supports both ranking and “citation-worthiness.”
6) Build “trust infrastructure” across the site
Authentic content can still underperform if the site looks untrustworthy.
Priorities:
- About, Contact, policies (returns, refunds, editorial)
- clear ownership and accountability
- citations to primary sources where relevant
- remove or consolidate thin pages
- prune zombie content and doorway-like variants
Also don’t neglect basics like crawlability and architecture. Google can’t reward what it can’t understand.
7) Treat AI as a co-writer, not a publisher
A strong AI workflow in 2026 looks like:
- AI for outlining, ideation, editing, and structure
- humans for experience, assertions, nuance, and responsibility
- mandatory “information gain” checklist before publish
- fact-checking + source linking where appropriate
Remember, Google has said that generative AI is fine if the output meets Search Essentials and avoids low-value scaled publishing.
Ultimately, whether Google’s so-called “Authenticity Update” is the real deal or a bunch of assumptions made by digital marketing bloggers misses the point. Search engines have been saying for years that they favor helpful, reliable content that is written with people in mind. And the ease with which low-quality content is produced thanks to AI is making it necessary for website owners and marketers to create high-quality content that stands out.
Click the link to learn more about our keys to success in GEO/organic visibility.
