AI Search engines are reshaping how brands earn visibility, and the data now coming through is stark. Across ChatGPT, Gemini, and Google’s AI features, the gap between being cited and being recognised is widening fast. Our team has been tracking these shifts closely, and five recent developments confirm what we’ve been advising clients: traditional SEO tactics alone no longer guarantee brand visibility in AI-driven results. Here’s what matters right now and what we’re doing about it.

Key Takeaways

• 62% of AI citations fail to produce a brand mention, creating a massive “ghost citation” problem for businesses relying on AI referral traffic.
• Category entry points (CEPs) are proving to be a powerful framework for earning consistent visibility across ChatGPT, Google AI Mode, and AI Overviews.
• Video SEO now extends beyond YouTube rankings into Google search results and AI-generated citations.
• Google’s E-E-A-T framework remains the foundational quality signal that underpins both traditional and AI search performance.
• Brands that actively manage their AI perception — as rtCamp demonstrated — can close visibility gaps within weeks, not months.

Ghost Citations Are Eroding Brand Visibility at Scale

This is the single most important data point we’ve seen this quarter. A joint study analysed 3,981 domain appearances across ChatGPT, Gemini, Google AI Overviews, and Google AI Mode. The finding: 62% of AI citations don’t lead to brand mentions. That means AI engines are pulling content from your site, using it to inform answers, and giving you zero brand credit in return.

We call these “ghost citations.” They’re common because AI models treat source material as raw information rather than branded content. For our clients, this means we’re now auditing AI outputs directly — checking whether brand names actually appear alongside cited URLs. If they don’t, we restructure on-page content to embed brand signals more explicitly within the passages AI models are most likely to extract.

Category Entry Points Are Reshaping AI Content Strategy

CEPs — the mental triggers buyers associate with a category before they think of a brand — are no longer just a brand strategy concept. New research shows that CEP-anchored content performs measurably better across ChatGPT, Google AI Mode, and AI Overviews. When content maps directly to the situations, needs, and motivations that prompt a purchase decision, AI engines surface it more reliably.

We’re building CEP maps for every client engagement now. The process is straightforward: identify the five to ten buying triggers relevant to the client’s category, then create dedicated content assets that address each trigger with clear, authoritative answers. This isn’t about keyword stuffing. It’s about matching the way AI models retrieve and synthesise information.

Video SEO Now Feeds Three Distinct Channels

Video content is no longer just a YouTube play. A comprehensive breakdown of video SEO strategy for YouTube, Google, and AI confirms that optimised video now earns engagement across traditional search results and AI-generated citations simultaneously. We’re updating our video production workflows to include structured metadata, transcript optimisation, and schema markup that AI crawlers can parse cleanly.

E-E-A-T Remains the Quality Baseline for AI and Traditional Search

Google’s Quality Raters still evaluate content through the E-E-A-T framework — Experience, Expertise, Authoritativeness, and Trustworthiness. This hasn’t changed with the rise of AI search. If anything, it matters more. AI models preferentially cite sources that demonstrate clear topical authority and first-hand experience. We treat E-E-A-T compliance as a non-negotiable baseline across every content brief we produce.

Closing the AI Perception Gap Is a Solvable Problem

rtCamp, a wordpress enterprise agency, discovered that AI engines were misrepresenting their capabilities — costing them deals. Within one month, they improved AI visibility and pushed favourable AI sentiment to 100% by systematically updating their public-facing content and digital footprint. This case study is proof that AI perception management isn’t abstract. It’s tactical, measurable, and fast when done correctly.

The brands winning in AI search right now are the ones treating generative engines as a distinct channel requiring its own strategy. Ghost citations, CEP mapping, video optimisation, E-E-A-T signals, and active perception management — these are the five levers we’re pulling for every client. The window to act is open, but it won’t stay open indefinitely as competitors catch up.

Frequently Asked Questions

What are ghost citations in AI search?

Ghost citations occur when an AI engine uses your content as a source but fails to mention your brand name in its response. Research shows this happens in 62% of AI citations, meaning brands lose recognition despite their content being referenced.

How do web designers use category entry points for AI visibility?

Category entry points are the buying triggers that prompt customers to think about a product category. Web designers and SEO teams create dedicated content mapped to each trigger, which AI engines then surface more consistently in generated answers.

Why does E-E-A-T still matter for AI search results?

AI models preferentially cite sources that demonstrate genuine expertise and trustworthiness. E-E-A-T compliance ensures your content meets the quality threshold that both Google’s traditional algorithm and AI engines use when selecting sources.

How can a business improve its AI search perception quickly?

By auditing what AI engines currently say about your brand and systematically updating public-facing content to correct inaccuracies. As rtCamp demonstrated, it’s possible to reach 100% favourable AI sentiment within a single month through targeted content and digital footprint management.

What is video SEO and why does it matter for AI citations?

Video SEO is the practice of optimising video content for discovery across YouTube, Google search, and AI-generated results. With AI engines now citing video sources alongside text, properly structured metadata and transcripts directly increase the chances of earning AI visibility.