The safety of the scroll has gone.
When Google launched its AI Overviews, it removed the last buffer between a story and its consequence. Users no longer need to click. They read the summary at the top — a short, confident verdict built from the web’s most “trusted” voices.
That box now acts as a Zero-Click Narrative. It condenses multiple high-authority sources into one algorithmic statement of fact. If a damaging article exists, it can resurface inside that summary years later — unchanged, unaudited, amplified.
For reputation management, this is structural. It isn’t a search engine update; it’s a shift in how credibility itself is assigned. Suppression and de-indexing still matter — they remain the fastest way to control exposure — but they can’t stand alone. Once the AI forms its “view” of your brand, recovery depends on reshaping the data it consumes.
According to Semrush, over 13% of Google queries now trigger an AI Overview, a figure rising month on month. Data shows that when these appear, the click-through rate for the first organic link drops from 7.3% to 2.6%. The audience no longer explores; they absorb. That makes the summary box the single most powerful reputation surface online.
For brands, executives, and legal teams, that surface is where Igniyte now works — combining suppression, structured authority, and Generative Engine Optimisation (GEO) to control how AI reads and retells your story.
The Fatal Familiarity: Authority Is Now Weaponised
The fundamentals of visibility — authority, trust, relevance — used to protect you. They still drive discovery, but in AI search, they also drive exposure.
E-E-A-T: The Citation Magnet
Google’s AI framework leans heavily on E-E-A-T — Experience, Expertise, Authoritativeness, and Trustworthiness. These are the quality signals its models use to decide which sources to rely on when building AI summaries.
Content that falls under what Google calls “Your Money or Your Life” (YMYL) topics is treated with even greater scrutiny. YMYL covers subjects that could affect a person’s finances, career, wellbeing, or safety — such as investment decisions, executive conduct, corporate risk, or legal disputes. In other words, anything with financial or reputational consequences.
AI models weigh E-E-A-T signals more heavily for YMYL content because inaccuracies in these areas carry a higher risk.
For high-net-worth individuals and corporates, most online coverage sits squarely in that category. Which means a single high-authority negative article — from a trusted financial or legal source — can become the version of truth the AI chooses to display.
The Geo-Targeted Toxin
AI doesn’t just weigh authority; it localises it. A Manchester business story carries more weight in a Manchester search than a national write-up. That geo-relevance turns local coverage into a potent reputational hazard. Investors, customers, or journalists searching near the source see the local headline first, cited as “context” in the AI summary.
In practice, a single negative local article can dominate region-specific results, even when neutralised elsewhere. It’s the same ORM problem, multiplied by geography.
Igniyte’s GEO strategy rebuilds that local trust signal — using structured press, verified listings, and regional Knowledge Graph optimisation to ensure the AI finds your material first.
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Consensus Turns Temporary Into Permanent
In the old search landscape, you fought for position. Push a negative link down, build authority elsewhere, and the story faded. That’s no longer how the machine works.
AI doesn’t rank pages. It reads them, compares them, and extracts meaning. What it looks for are semantic triples — simple factual relationships like “[Company] was accused of [Action] in [Year].” Once that relationship appears across several high-authority sources, it becomes the default truth inside the AI’s model.
Fighting an Algorithm, Not a Link
Most generative overviews synthesise information from five to seven sources. Remove half of them, and the summary doesn’t change. The remaining few carry enough authority to preserve the same narrative. That’s why simple suppression campaigns, while still necessary for visibility, can’t reverse entrenched consensus. They buy time; they don’t rewrite the model.
Pew Research found users click less when AI summaries are present — meaning fewer chances to introduce corrective information through owned or earned media. At the same time, UK publishers have reported significant traffic drops as Google’s overviews expand [Press Gazette, 2025]. The summary is now the destination, not the gateway.
No Opt-Out, Only a Feedback Form
There’s no technical method to block AI from referencing public URLs. No robots.txt line, no noindex tag, no appeal process. The only control Google offers is a “Feedback” button below the summary. It’s slow, opaque, and reactive.
The only reliable option is to overwrite the signal: feed the algorithm new, structured, higher-authority data until its pattern of truth changes. And that’s where the next evolution of ORM begins.
Next-Generation ORM. Structure for Citation (AEO/GEO)
Igniyte’s work now extends beyond suppression. Igniyte have long now offered Answer Engine Optimisation (AEO) and Generative Engine Optimisation (GEO) strategies — structuring content so that AI models treat it as the most reliable explanation of a subject.
Out-Structure the Negative Narrative
Generative engines reward precision. They pull from text that’s clear, declarative, and formatted for machine parsing. According to a Princeton study, content that includes verifiable statistics and expert attribution is 30–40% more likely to be extracted into AI results.
To make that happen, brand assets need to be built with the AI in mind:
- Start with short, direct paragraphs that answer a question in under sixty words.
- Use H2s and H3s phrased as queries: “What happened in 2024?”, “How did [Company] respond?”
- Embed expert commentary, sourced data, and readable statistics.
- Apply Schema Markup (FAQ, HowTo, Organisation) to signal structure.
When done well, these small formatting decisions can shift which paragraph — and which narrative — the AI lifts. Readability and authoritative structure directly correlate with extractability.
Build a Geo-Targeted Shield
AI weighs local relevance heavily. So a negative piece in a city or regional outlet can shape results for nearby users. Igniyte’s geo-entity saturation model reverses that effect.
It uses structured local content — verified Google Business listings, charity partnerships, press statements, and community involvement — to populate the local Knowledge Graph with positive, high-confidence data. When a user searches in that region, the AI detects stronger, newer local signals from your material and begins citing them instead.
That’s suppression working in tandem with structure — a defensive layer that adapts to generative search rather than fighting it.
ORM’s New Mandate – The Battle for Citation
The metric has changed. Visibility is no longer measured by rank; it’s measured by citation inside AI summaries. Your objective is to control what the algorithm trusts enough to quote.
Suppression remains step one — stabilising the surface. The second step is structural dominance: ensuring your data, language, and authority are what the model prefers to use.
That’s where Igniyte now leads: combining traditional ORM precision with next-generation GEO methodology to secure reputational control in an environment where summaries, not scrolls, define truth.
Don’t wait for an AI summary to fossilise your worst headline. Request an AI Reputation Audit today and take back control of your narrative.
Managing Director at Igniyte – The Reputation Experts
Roz is an industry spokesperson on all areas of online reputation management and our resident digital media expert. She regularly writes about reputation management research, online reputation risk and industry best practice.
