Google’s AI Overviews have fundamentally changed the way users interact with search engine results pages (SERPs). For years, B2B software companies and SaaS brands relied on a reliable content marketing playbook: publish “best [category] software” listicles, rank their own product as the undisputed number-one choice, and capture high-intent organic traffic. This strategy of publishing self-serving listicles was designed to control the narrative and drive direct conversions.
However, recent data suggests that Google’s search algorithms are turning this tactic against the very brands that pioneered it. According to an extensive analysis conducted by SEO expert Lily Ray, Google’s AI Overviews frequently cite these self-promotional listicles as sources of information, but they recommend the brands’ direct competitors approximately 69% of the time.
This paradigm shift in search behavior has massive implications for search engine optimization (SEO), Generative Engine Optimization (GEO), and digital PR. It signals a future where appearing as an informational citation in an AI-generated answer does not guarantee commercial visibility—and may actually help your closest competitors win customers.
The Data Behind the AI Overview Disconnect
To understand how Google’s AI treats self-promotional content, Lily Ray conducted a multi-month analysis tracking 100 high-value B2B “best [category] software” search queries. Using Ahrefs Brand Radar, Ray monitored the AI Overview text and the specifically cited sources across three key checkpoints: April 15, May 15, and June 8.
The findings paint a stark picture of how Google’s Retrieval-Augmented Generation (RAG) system processes self-ranking content:
- Of the 100 queries tracked, 80 prompts successfully triggered a Google AI Overview.
- Across these 80 AI-generated answers, self-promotional listicles were cited as source materials a total of 323 times.
- In 224 of those instances, Google cited the brand’s page to build its response but excluded that brand from its actual product recommendations.
This means that in 69% of cases, brands that spent time, effort, and budget creating comparison content were used purely as “data food” for Google’s AI, while the actual leads and recommendations were handed to their competitors.
Why Google Cites Your Site to Recommend Your Competitors
To understand why this is happening, it is necessary to examine how large language models (LLMs) and search engines collaborate in AI Overviews. Google uses RAG to pull factual data from the live web to ground its AI responses, ensuring the information provided is current and accurate.
When a user searches for the “best LMS for selling courses,” Google’s system scans top-ranking pages to find lists of relevant software. If a brand like Oasis LMS has a well-structured, comprehensive listicle on this topic, Google’s AI may pull the names of the top tools from that page. However, Google’s algorithmic ranking systems also evaluate the overall authority, neutrality, and market sentiment of the brands mentioned.
In the case of the “best LMS for selling courses” query, Google cited the Oasis LMS article as a source. Yet, in the actual recommendation list generated by the AI Overview, Oasis LMS was nowhere to be found. Instead, the AI recommended Kajabi, Thinkific, LearnWorlds, and Teachable—all of which were competitors listed and analyzed within the Oasis LMS article.
This pattern was not an isolated incident. Ray documented the exact same behavior across a wide variety of highly competitive B2B software categories, including:
- Help desk software
- Task management applications
- Online survey tools
- Customer Relationship Management (CRM) platforms
- SEO software and utility tools
By publishing exhaustive lists of competitors alongside their own products, brands are inadvertently training Google’s AI on who the major players in their space are. The AI then filters out the hosting brand due to perceived bias, while presenting the mentioned competitors to the searcher.
Entity Authority and the Power of Stronger Brands
If Google is filtering out self-serving recommendations, how does it decide which brands to actually recommend? The data suggests that Google’s algorithmic trust is heavily tied to independent authority and the broader “entity graph.”
Brands that already led their respective categories, possessed strong backlink profiles, and were widely mentioned across independent third-party websites were far more likely to be featured in the final AI Overview recommendations. Google’s algorithms appear capable of cross-referencing information. If a brand claims to be the “best” on its own website, but third-party forums, news outlets, and review portals do not corroborate that claim, the AI is likely to dismiss the self-recommendation as biased.
This creates a clear division in search engine visibility:
- Citations: Awarded to websites that have good informational structure, clear lists, and readable content that the AI can easily parse to gather facts.
- Recommendations: Awarded to brands with genuine market authority, strong digital PR presence, and unbiased end-user trust.
Organic Visibility Declines and the Core Update Impact
This shift in how Google processes listicles is not just affecting AI Overviews; it is also dragging down traditional organic search rankings. Ray’s research highlighted a downward trend in organic visibility for dozens of sites that relied heavily on self-promotional “best-of” content hubs.
The organic declines first began to materialize around January 20. Many of the affected domains had aggressively scaled SEO and Generative Engine Optimization (GEO) tactics. This included publishing large volumes of AI-generated articles, thin product comparison pages, and templated listicles that systematically ranked their own brand as the top option.
These ranking declines accelerated dramatically during Google’s May 2026 core update. As Google continues to refine its helpful content classifiers, websites that exhibit high levels of self-promotional bias are losing their traditional organic footprint. Some SaaS and B2B brands have seen their overall search visibility plunge by 30% to 50% after relying too heavily on these self-ranked comparison pages.
The Rise of Third-Party Publishers and User-Generated Content
As Google demotes self-serving brand listicles, it is turning to other sources to fill the gap. AI Overviews for commercial “best” queries are increasingly citing independent, third-party publishers and user-generated content (UGC) platforms.
Among the most-cited domains in AI Overview responses containing the word “best” are:
- Reddit: Google has heavily integrated user discussions into its search results, viewing real-world community discussions as highly authentic and unbiased.
- Forbes: Massive media publishers with strong domain authority continue to capture high-value informational citations.
- YouTube: Video walkthroughs, reviews, and hands-on tutorials are heavily favored by the AI as proof of real-world usage.
This shift emphasizes that Google prefers to source recommendations from platforms where the creator does not have a direct financial stake in selling the specific software being reviewed.
Legal and Regulatory Risks of Self-Ranking Content
Beyond the loss of organic traffic and AI recommendations, B2B brands using self-serving listicles face growing regulatory challenges. Presenting company-controlled content as unbiased, objective, or independent review material can carry substantial legal risk.
Under the Federal Trade Commission’s (FTC) Consumer Review Rule, marketing practices that mislead consumers regarding the independence of reviews are subject to heavy penalties. As previously reported, these low-quality listicle trends may create legal liabilities if:
- The reviews and rankings are not based on real, documented testing or usage of the software.
- The material financial relationship between the website owner and the recommended brand is not clearly and conspicuously disclosed.
- The website attempts to mimic an independent third-party review portal when it is actually owned and operated by one of the software vendors listed.
As search engines and regulatory bodies both crack down on deceptive review practices, the viability of self-ranking listicles as a long-term marketing channel is rapidly diminishing.
How B2B Brands Must Adapt Their SEO Strategy
The revelation that calling your own brand “the best” could actively drive business to your competitors requires a complete rethink of modern B2B SEO strategy. To survive and thrive in an AI-first search environment, brands should consider the following strategic shifts:
1. Transition from Self-Promotion to Objective Comparison
If you publish comparison content on your own website, maintain strict objectivity. Provide real data, transparent pros and cons, and clear use cases for when a competitor might actually be a better fit for a buyer. Google’s algorithms are increasingly sophisticated at identifying natural, unbiased language.
2. Double Down on Digital PR and Off-Page Brand Mentions
Since Google relies on third-party sites to validate who is truly the “best” in a category, your off-page SEO and digital PR efforts are more important than ever. Focus on securing un-sponsored reviews, media coverage, and mentions on reputable industry publications, tech blogs, and independent review platforms.
3. Engage with UGC and Community Platforms
Because platforms like Reddit and YouTube are dominating AI Overview citations, marketing teams must actively participate in these communities. Encourage your actual customer base to share their honest experiences on forums, subreddits, and third-party review sites. An active, organic footprint on Reddit can do more for your AI Overview visibility than dozens of self-published blog posts.
4. Focus on Entity-Based Search and Schema Markup
Help search engines clearly understand your product’s features, pricing, and integrations by using robust, structured Schema markup. This makes it easier for search bots to extract accurate facts about your product directly, without having to rely on biased listicle narratives.
The Future of AI Search Optimization
The era of gaming search engines with self-serving “best of” listicles is drawing to a close. As Lily Ray’s detailed analysis demonstrates, Google’s AI Overviews are smart enough to extract information from your content while filtering out your self-promotional bias.
To capture high-value conversions in this new search landscape, brands must focus on building authentic, third-party authority. In a world where a citation is no longer a recommendation, real brand equity, user trust, and independent validation are the ultimate ranking factors.