A customer asks ChatGPT for the best software provider, marketing agency, or eCommerce platform in a category.
A brand with years of experience, strong customer results, and a comprehensive website appears nowhere in the response.
Instead, competitors are listed first.
Sound familiar?
The competition for visibility now includes AI-generated answers, where recommendation decisions rely on different signals rather than traditional search results.
About 53% of consumers distrust or lack confidence in the reliability and impartiality of AI-powered search results, according to Gartner’s 2025 survey.
So, brands need to understand which signals influence AI recommendations and why competitors may appear more frequently.
Christina Adame, President of SEO and GEO at Intero Digital, said three factors often determine which brands surface in AI responses:
- Content structure
- Third-party validation
- Topical authority
“Well-organized, directly answerable content can influence retrieval, and competitors with cleaner structured data and FAQs get pulled forward more easily,” she says.
Who Is Christina Adame?
Christina Adame is the President of SEO and GEO at Intero Digital. She has over 10 years of experience specializing in SEO, GEO, and AI-driven search. As a Google-certified expert, she’s helped thousands of growth-focused businesses boost visibility, drive traffic, and build meaningful connections with their audiences.
AI systems rely on information that can be interpreted and retrieved efficiently.
External credibility also influences how brands are represented.
Adame also notes that large language models consider mentions from trusted third-party sources, including review sites, comparison articles, and online forums.
A competitor with stronger external coverage can appear more frequently in AI recommendations even when another brand has a stronger-owned website.
However, content quality remains another factor influencing how AI systems evaluate information.
In fact, 49% of U.S. consumers say generative AI has made the quality of available content worse, according to Gartner’s June 2026 research.
More AI-generated content means brands need clear expertise signals and credible information sources that help models identify reliable answers.
How to Measure AI Visibility
AI visibility requires additional measurement focused on how brands appear inside generated responses.
Brands tracking AI visibility can identify the prompts where they appear, where competitors receive mentions, and which areas need further analysis.
Without this data, it can be harder for marketers to understand how large language models select and cite sources.
One solution is to build AI visibility measurement into ongoing marketing analysis.
“Competitors with measurement in place can iterate faster,” Adame says.
“Closing content gaps, building the specific third-party mentions models pull from, and reallocating budget toward what's actually moving citation share.”
But evaluating AI visibility requires more than tracking whether a brand appears in an answer.
Adame describes the process as a layered measurement approach that includes citations, mentions, prompts, traffic, and conversions.
“Citations and mentions are the foundation. Are you showing up in AI answers at all, and how often are you showing up relative to competitors?” she asks.
Prompt-level tracking is the second component.
“Which specific queries surface your brand versus competitors?” Adame says.
Marketers need to understand:
- Which searches trigger competitor recommendations
- Which queries include their brand
- How AI systems describe different companies
And while traffic and conversions remain important, they do need to be attributed carefully.
“AI-referred traffic data is often incomplete or fragmented,” Adame adds.
The strongest analysis combines:
- Citation share of voice
- Sentiment within AI responses
- Downstream engagement rather than relying on a single metric
This makes visibility inside AI responses a consideration-stage issue, even when AI does not make the final purchase decision.
Only 11% of U.S. consumers are willing to let AI make purchase decisions, according to Gartner’s May 2026 research.
Meanwhile, 31% are willing to use AI to narrow product choices for household purchases and 28% for personal electronics.
These figures suggest brands need to monitor how they appear in AI recommendations during early research stages, where consideration is influenced.
Knowing where a brand appears is only part of the story, because the bigger question is how that visibility compares with competitors.
Benchmarking requires a consistent approach that reflects real customer questions.
Adame recommends creating a prompt set based on customer searches across the buying journey, then monitoring those prompts systematically over time.
“Relative to our named competitors, in our highest-intent prompts, who wins the recommendation and why?” she says.
This approach allows marketers to compare citation frequency, context, and positioning.
AI visibility platforms can help track these patterns over time rather than relying on isolated checks.
The goal is identifying where competitors appear, why they appear, and which signals contribute to their visibility.
How GEO Identifies Why Competitors Get Recommended
Intero Digital approaches AI visibility through structured audits that compare a brand’s presence against competitors across defined prompt sets.
The process examines potential causes, including content gaps, missing third-party mentions, structured data issues, and sentiment challenges.
These findings can inform GEO strategies by identifying where brands need stronger content coverage, external validation, or technical improvements that help AI systems interpret information.
The growing importance of AI visibility does not replace traditional search practices.
It adds another layer to how brands evaluate digital presence and customer discovery.
For marketers concerned that ChatGPT keeps recommending competitors, Adame advises against treating the issue as a traditional SEO challenge alone.
“Don't treat this like it’s only a traditional SEO problem. Keep the fundamentals, but add direct measurement of prompts, mentions, citations, and recommendations.
“Get a real prompt-level baseline of where you stand today because the instinct to guess will keep you a step behind the competitors that are already measuring this deliberately.”
Visibility inside these systems will depend on whether brands understand the signals influencing recommendations.
Companies that measure where they appear, where they are missing, and why competitors are winning will have clearer direction for improving their position.
