What Not to Do in GEO | Actions That Make AI Less Likely to Trust Your Brand
What not to do in GEO refers to actions and tactics that unintentionally reduce how much AI systems trust your brand's content.
GEO is not just about what to do — what you avoid doing is considered equally important.
Many brands trying to optimize for AI visibility end up creating content that AI is actually less likely to trust or cite.
The actions described here do not trigger penalties — but they are considered to reduce the trust signals that AI systems use when evaluating and selecting information.
What You'll Learn in This Article
- The content characteristics that make AI less likely to trust a source
- Five actions that tend to undermine GEO effectiveness
- The pitfall of chasing citation counts instead of building brand mentions
- Why treating GEO as entirely separate from SEO is counterproductive
For background on how AI evaluates information, see How AI Chooses Information.
1. Publishing Unnatural, AI-Targeted Content at Scale
Trying too hard to write "content optimized for AI" — and producing large volumes of it — is considered counterproductive to GEO.
Specific behaviors that fall into this category include:
- Keyword stuffing: Repeating specific terms at unnatural frequencies can reduce the perceived credibility of content when AI evaluates it for trustworthiness
- Publishing AI-generated content without quality review: Releasing large volumes of unreviewed AI-generated text is considered to reduce the overall trustworthiness of a content library
- Overusing "AI-optimized" formatting patterns: Definitions, FAQs, and BLUF are genuinely effective — but using these formats with thin, low-value content is considered unlikely to improve AI evaluation scores
As Entrepreneur (Simon Moser, April 2026) notes, getting recommended by AI platforms comes down to the same trust signals that have always mattered.
AI is considered to prioritize whether information is genuinely trustworthy over the structural patterns of how it is written.
2. Relying Entirely on Content Without Original Information
Content that aggregates information from other sources without adding original data, firsthand perspectives, or unique insights is considered less likely to be trusted by AI.
Because AI compares and evaluates multiple sources simultaneously, it is considered to prioritize "information that exists only here" over "information available everywhere."
Content that lacks original data or a distinctive viewpoint — even if well-structured — gives AI fewer reasons to select it as a citation source.
Effective alternatives include:
- Including proprietary data, research findings, or survey results
- Adding the author's firsthand experience or expert perspective
- Developing a distinct angle or insight that cannot be found on other sites
3. Chasing Citation Counts Instead of Building Mentions
Focusing exclusively on increasing citation counts — the number of times your URL appears as a linked source in AI responses — is considered a misaligned GEO priority.
Simon Moser writes in Entrepreneur:
I've watched brands obsess over citation counts while neglecting the authority-building work that drives mentions. They optimize page structure, add schema markup and tweak headings — all worthwhile — but ignore the editorial presence that gets an AI system to recommend them in the first place.
In most commercial contexts, brand mentions — the AI recommending your company by name, whether or not it links to your site — are considered to have a greater business impact than linked citations alone.
Page structure optimization, schema markup, and heading adjustments are all worthwhile, but they are not considered sufficient on their own to get an AI system to recommend a brand in the first place.
For more on the difference between AI citations and AI mentions, see What Is an AI Citation?
4. Going Quiet After Launch
Stopping content publication and brand communication after a product or service launch is considered likely to reduce AI trust signals over time.
AI training data is updated periodically, and brands that go quiet risk gradually fading from AI awareness.
When external media mentions, reviews, and industry discussion dry up, entity authority is considered to weaken as well.
Effective ongoing practices include:
- Maintaining a consistent cadence of content updates and external media coverage
- Regularly creating brand mention opportunities through press releases, industry events, and podcast appearances
- Monitoring AI citation status periodically to catch any gaps in brand visibility
5. Treating GEO as Completely Separate from SEO
Treating GEO as an entirely new and independent discipline — separate from SEO, managed by a separate team, or pursued at the expense of existing SEO work — is considered counterproductive.
The Entrepreneur article identifies this as one of the five core GEO mistakes: treating generative engine optimization "like an exotic new discipline."
The view that "good SEO is good GEO" is widely held internationally — the quality, relevance, and authority built through SEO are considered equally valuable for GEO.
GEO-specific tactics — BLUF structure, definition sentences, FAQ sections, and entity information setup — are considered most efficiently implemented as extensions of existing SEO work, not replacements for it.
For a detailed overview of how GEO and SEO relate, see GEO vs SEO.
6. Measuring with Metrics That Don't Connect to Real Outcomes
Tracking GEO effectiveness using dashboard numbers that are disconnected from actual business outcomes is considered a common but easily avoidable mistake.
Moser identifies this as one of the five core mistakes: "most teams are tracking their GEO performance with dashboard numbers that don't connect to anything real."
For example, focusing entirely on citation frequency for a specific query while not tracking brand awareness or pipeline impact is considered a misaligned measurement approach.
More meaningful metrics to consider:
- Share of Model (AI exposure share): How many times your brand appears across all relevant queries
- Brand mention trends: Monitoring both citations (linked) and mentions (text only) together
- Connection to business outcomes: Tracking AI-driven inquiries or shifts in brand awareness alongside AI visibility metrics
With the GEO tool Genview, you can monitor AI citation rates and brand mention counts — helping you build a measurement approach grounded in real visibility data.
Frequently Asked Questions
- Q: Is writing "AI-optimized" content a bad practice?
- A: Writing content that is unnatural or keyword-heavy in an attempt to "optimize for AI" is considered counterproductive. Definition sentences, BLUF, and FAQ sections are genuinely effective — but only when the underlying content is trustworthy and substantive. AI is considered to evaluate information quality and credibility rather than surface-level formatting patterns.
- Q: Is focusing on increasing citation counts a problem?
- A: Focusing exclusively on citation counts is considered a misaligned priority. In many commercial contexts, brand mentions — the AI recommending your company by name — are considered to have greater business impact than linked citations. Building authority through external media presence is considered the fundamental approach for generating mentions.
- Q: Should GEO and SEO be managed by separate teams?
- A: Running GEO as a completely separate function is considered counterproductive. GEO is most efficiently pursued as an extension of existing SEO work. Adding GEO elements — BLUF, definitions, FAQ sections — to existing SEO content is considered the most practical approach for most teams.
