The Shift in Search: How Google’s AI Overviews Handle Self-Promotional Content
For years, B2B software companies and SaaS brands have relied on a predictable playbook to capture high-intent search traffic: the “best of” listicle. By publishing comprehensive roundups of the top software in their niche—and conveniently ranking their own product as the number-one choice—brands managed to control the narrative, drive organic traffic, and capture qualified leads.
However, the integration of generative AI into search engines has disrupted this strategy. Google AI Overviews, designed to synthesize complex queries and provide direct recommendations, are processing these self-serving listicles in unexpected ways. Recent research reveals that while Google’s AI frequently crawls and cites these company-owned listicles as information sources, it actively bypasses those same brands when recommending products to users.
According to an in-depth analysis of B2B software search queries conducted by SEO expert Lily Ray, Google AI Overviews cited self-promotional “best” listicles but excluded the publishing brands from its actual product recommendations in 69% of analyzed cases. This phenomenon exposes a critical gap in modern search engine optimization: a citation in an AI Overview is no longer synonymous with a recommendation.
Deconstructing the Data: Lily Ray’s Findings on AI Citations
To understand how Google’s algorithms handle self-promotional brand content, Lily Ray monitored 100 high-value B2B search queries based on the formula “best [category] software.” The study analyzed AI Overview behavior across three distinct checkpoints: April 15, May 15, and June 8.
Using Ahrefs Brand Radar to track search engine result page (SERP) fluctuations, AI Overview answer text, and cited sources, the research highlighted a clear discrepancy between the sources Google relies on for data and the brands it recommends to searchers:
- High AI Penetration: Out of the 100 search prompts analyzed, 80 triggered an AI Overview, proving that generative search is heavily active in transactional B2B software verticals.
- Heavy Citation of Listicles: Across these 80 AI Overviews, self-promotional listicles published by software brands were cited a total of 323 times.
- The Recommendation Disconnect: In 224 of those instances, Google cited the brand’s listicle as a source of information but completely omitted that brand from its list of recommended solutions. This represents a 69.3% rate of citation without recommendation.
These metrics indicate that while B2B brands are successfully optimizing their content to be read and understood by Google’s large language models (LLMs), the AI is smart enough to extract the competitive data from those pages while ignoring the self-serving bias of the host site.
The Oasis LMS Example: The Ultimate SEO Backfire
To understand how this dynamic plays out on the live SERPs, we can look at a specific query highlighted in Lily Ray’s analysis: “best LMS for selling courses.”
For this query, Google’s AI Overview generated a summary of the top learning management systems (LMS) available for content creators. To populate this list, the AI crawled and cited a comprehensive “best of” article published by Oasis LMS. However, instead of recommending Oasis LMS to the searcher, Google’s AI Overview recommended its direct competitors:
- Kajabi
- Thinkific
- LearnWorlds
- Teachable
Crucially, all four of these competing platforms were discussed, analyzed, and linked to within the Oasis LMS article. Google’s LLM essentially read the Oasis LMS blog post, extracted the competitor data, recognized that these four platforms were industry leaders, and presented them to the user as the premier choices—all while leaving Oasis LMS out of the final recommendations.
This pattern is not isolated to the e-learning space. Similar search behavior and competitor-first recommendation structures have been documented across several major software verticals, including:
- Help desk and customer support ticketing systems
- Task and project management platforms
- Online survey and feedback tools
- Customer Relationship Management (CRM) suites
- Search Engine Optimization (SEO) software
Why Google AI Cites Listicles But Recommends Competitors
To understand why this happens, it is necessary to examine how search generative engines process information differently than traditional keyword-matching search algorithms.
Entity Recognition and LLM Training
Google’s AI models are trained to recognize “entities” (established brands, products, individuals, and concepts) and understand the relationships between them. When an AI crawler analyzes a B2B brand’s listicle, it does not simply view the page as a collection of keywords. Instead, it extracts the entities mentioned on that page.
If an Oasis LMS article lists Kajabi, Thinkific, and Teachable, the AI records that these entities are frequently grouped together under the category of “LMS for selling courses.” Because Kajabi and Teachable are mentioned across thousands of other independent websites, forums, and reviews, the AI recognizes them as high-authority entities in this niche. Oasis LMS, which may have a smaller digital footprint, does not carry the same level of independent verification. Consequently, the AI recommends the more dominant entities while using the smaller brand’s page merely as a convenient content aggregator.
The Discrepancy Between Citation and Endorsement
In traditional SEO, earning a ranking or a snippet meant your brand captured the user’s attention. In the era of AI Overviews, a citation is simply an attribution of data source. Google’s AI must cite its sources to maintain transparency and avoid legal or accuracy issues. However, citing a webpage as the source of a list does not mean the AI endorses the host of that webpage.
If a brand ranks its own product as number one on its own website, Google’s AI often discounts this self-ranking as biased. The algorithm compares the claims made on the brand’s website with sentiment and data across the broader web. If independent sources do not corroborate the brand’s self-proclaimed status, the AI will default to recommending competitors that have broader, unbiased market validation.
The Decline of Organic Visibility for Self-Promotional Brands
The strategic shift in how Google processes “best of” lists has already had financial and visibility consequences for B2B brands. Lily Ray reported that many websites relying heavily on self-promotional listicles have suffered major declines in organic search traffic.
This downward trend did not happen overnight. The organic visibility declines began around January 20 across dozens of domains analyzed in the study. These affected sites had often scaled their SEO and Generative Engine Optimization (GEO) efforts by deploying:
- Mass-produced, AI-generated comparison and review articles.
- Highly templated “Brand A vs. Brand B” comparison pages.
- Dozens of “best” category lists that systematically ranked their own brand in the top spot without editorial objectivity.
These traffic drops accelerated dramatically during Google’s May 2026 core update. As Google continues to refine its algorithms to combat helpful content violations and search engine manipulation, sites that built their organic traffic on biased, self-published reviews are losing their rankings. Previous data from Search Engine Land indicates that some B2B and SaaS brands have lost between 30% and 50% of their overall organic visibility due to a heavy reliance on self-ranked listicles.
The Rise of Third-Party Authorities and User-Generated Content
As self-serving brand content loses its influence in AI-generated answers, Google is shifting its reliance toward third-party authorities, media outlets, and platforms that feature authentic user discussions.
Lily Ray’s data confirms that for search queries containing the word “best,” Google AI Overviews are increasingly sourcing their recommendations from independent third-party domains and user-generated content (UGC) platforms. Among the most frequently cited domains in these transactional AI queries are:
- Reddit: The search engine’s partnership with Reddit has led to a sharp increase in Reddit threads being cited directly in AI Overviews. Google prioritizes real discussions, peer-to-peer recommendations, and unfiltered reviews over polished corporate marketing.
- Forbes: As a legacy media publisher with immense domain authority, Forbes and its various business councils frequently capture the citation spots for high-value B2B software terms.
- YouTube: Video walkthroughs, tutorials, and independent hands-on reviews on YouTube are heavily cited, as video content provides proof of real-world software usage.
This shift emphasizes that Google’s algorithm prefers information sources that do not have a direct financial stake in the products being recommended.
Legal and Regulatory Risks of Self-Ranked Listicles
Beyond the loss of organic search visibility and competitive positioning, publishing self-serving listicles that masquerade as independent editorial content carries legal risks.
The Federal Trade Commission (FTC) in the United States has steadily tightened its guidelines regarding consumer reviews and testimonials. Under the FTC’s Consumer Review Rule, businesses face scrutiny and potential legal action if they engage in deceptive review practices. Key areas of concern for B2B brands utilizing self-ranked listicles include:
- Deceptive Independent Reviews: Presenting a company-controlled review site or listicle as an independent, unbiased third-party source when it is actually promotional material designed to boost the parent brand.
- Lack of Authentic Use: Publishing detailed product reviews or comparison tables that are not based on actual, documented testing or real-world use of the software.
- Failure to Disclose Material Connections: Neglecting to clearly and conspicuously disclose that the site publishing the listicle owns, operates, or financially benefits from the top-ranked product on that list.
As search engines and regulatory bodies prioritize transparency, the legal and financial liabilities of these deceptive marketing tactics continue to grow.
How B2B Brands Can Adjust Their SEO and AI Optimization Strategies
The realization that a citation in an AI Overview does not guarantee a recommendation requires a fundamental shift in how B2B companies approach search engine optimization. Rather than trying to trick AI models with self-ranking listicles, brands must focus on building authentic authority across the web.
1. Focus on Off-Page Brand Sentiment and Digital PR
Because Google AI Overviews cross-reference brand mentions across the web to determine recommendations, off-page SEO and digital PR are more critical than ever. Brands should focus on:
- Securing reviews on trusted, independent software directories like G2, Capterra, and TrustRadius.
- Earning natural mentions in genuine editorial roundups on authoritative industry websites.
- Fostering active discussions about their product on community platforms like Reddit, Quora, and niche-specific forums.
2. Pivot from Self-Promotion to Objective Comparison
If you publish comparison content or listicles on your own site, prioritize objectivity. Instead of always claiming your software is the best for every scenario, provide honest, feature-based comparisons. Clearly state who your software is for, and just as importantly, who it is not for. Providing balanced, accurate data makes your content more trustworthy to both human readers and search engine crawlers.
3. Optimize for Entity-Based SEO
Ensure that search engines can easily associate your brand with your specific software category. You can achieve this by:
- Using clean schema markup (such as SoftwareApplication and Product schema) on your website.
- Maintaining an updated Google Business Profile and active profiles on major corporate directories.
- Publishing high-quality, original thought leadership content that demonstrates real expertise and authoritativeness (E-E-A-T).
4. Leverage Video and Multi-Format Content
Since Google frequently cites YouTube videos in AI Overviews, creating high-quality video walkthroughs, comparative demonstrations, and customer case studies can help capture visibility. Video content is harder to replicate with generative AI, making it a highly trusted source for search engines looking to verify authentic product capabilities.
The Future of B2B SEO in the Era of Generative AI
The digital marketing landscape is adjusting to the realities of generative search. Lily Ray’s analysis serves as a clear warning to B2B SaaS companies: gaming the system with biased, self-serving listicles is a strategy with diminishing returns.
As Google continues to roll out core algorithm updates and refine its AI Overviews, the focus is shifting away from simple keyword optimization toward holistic brand authority. To succeed in this new search environment, brands must focus on building products that users naturally recommend, earning authentic third-party validation, and ensuring their digital footprint extends far beyond the pages of their own website.