Pranas AI Study Reveals Growing “AI Visibility Gap” as AI Search Redefines Online Discovery

Analysis of more than 20,000 prompts finds that YouTube, Instagram, Wikipedia and other third-party platforms play a major role in shaping AI-generated answers.

Singapore, September 21, 2026 -- Pranas, an AI search visibility and brand intelligence platform, has released new research highlighting a growing challenge for marketing teams: a brand can have a strong digital presence yet remain underrepresented, incorrectly positioned or poorly attributed in AI-generated answers.

Pranas describes this difference between a brand’s established online presence and its representation across AI search platforms as the “AI Visibility Gap.”

The study analysed 20,839 unique prompts that generated Google AI Overviews during August 2026. After prompt normalisation and deduplication, researchers recorded 225,094 source citations across 13,996 root domains.

The findings suggest that appearing prominently in conventional search results or publishing content on an owned website may no longer be enough to shape how AI systems present a brand. AI-generated answers frequently draw evidence from third-party platforms, including video channels, social networks, marketplaces, publishers and reference websites.

As tools such as Google AI Overviews, ChatGPT, Gemini, Perplexity and Claude increasingly influence how people research products and businesses, marketing teams may need to measure more than rankings, clicks and conventional search visibility.

Third-Party Platforms Are Shaping AI Answers

The research found that non-owned platforms accounted for a significant share of the sources cited in AI-generated results.

YouTube was the most frequently cited domain in the dataset, receiving 26,558 citations. Instagram followed with 16,779 citations, while Wikipedia accounted for 11,951 citations. E-commerce marketplaces and other third-party websites also appeared prominently.

These findings indicate that AI systems do not build answers exclusively from company websites. They may rely on creator content, product listings, comparison pages, media coverage, public reference sources and online discussions when deciding which brands to mention and how to describe them.

This creates a new strategic challenge. A company may carefully manage the content published on its own website but have limited control over the external sources influencing its portrayal in AI-generated responses.

It also means that generative engine optimisation cannot be treated solely as an extension of on-page SEO. Brands may need a broader authority-building strategy that strengthens their presence across the wider information environment used by AI systems.

Brand Mentions Do Not Always Lead to Brand Traffic

A separate Pranas analysis of 10,227 travel-related prompts examined the relationship between brand mentions and direct website attribution.

Depending on the brand, the proportion of mentions accompanied by a direct link to its own website ranged from 63% to 82.5%.

The difference is commercially important. Two businesses could receive a similar number of mentions in AI-generated answers while experiencing very different outcomes. One brand may receive a direct citation that gives users a clear route to its website, while another may be mentioned using information attributed to a publisher, marketplace or competing platform.

This distinction creates two separate measures for marketing teams to consider:

• Brand visibility: Whether and how prominently the brand appears in an AI-generated answer.
• Traffic attribution: Whether the answer cites or links to the brand’s owned website.

Monitoring mentions alone may therefore provide an incomplete picture of AI-search performance. Citation sources help reveal who controls the pathway between the AI-generated answer and the potential customer.

AI Visibility Can Differ from Market Share

Pranas also studied 10,000 smartphone and electronics-related prompts to compare AI visibility with established market position.

In the study, the second-most visible brand appeared in 21.1% of relevant prompts despite accounting for only a single-digit share of local device shipments.

The result indicates that physical market share and AI visibility do not necessarily move together. Brands with extensive product documentation, comparison content, creator coverage and third-party discussion may appear more frequently than larger competitors.

This creates both an opportunity and a risk. Smaller businesses may gain disproportionate exposure by building a stronger information footprint, while established market leaders could lose visibility if AI systems find more useful or widely distributed evidence about their competitors.

“AI systems are becoming an intermediary between brands and buyers, but most brands are still unable to understand their visibility on AI assistants deeply or correctly map how to optimize it,” said Arshad Rahman, Co-Founder of Pranas.

“The next step is not to chase brand mentions in isolation. It is to understand where a brand appears, what evidence the AI relies on, and where customer questions are being answered by competitors or third parties instead.”

Three Priorities for Marketing Teams

Based on its findings, Pranas recommends that organisations adopt three priorities as AI-assisted discovery becomes a more significant part of the customer journey.

1. Measure citations alongside mentions

A mention confirms that a brand appears in an answer. A citation identifies the source that the AI system used to support that answer.

Tracking both can help marketing teams determine whether their visibility is being supported by owned content, independent publishers, creators, marketplaces or other third-party domains.

2. Build authority beyond owned channels

Company websites remain important, but they represent only one part of the information environment available to AI systems.

Brands may need to strengthen their presence across trusted publications, creator platforms, industry resources, marketplaces and other relevant channels. Accurate and consistent third-party coverage can help AI systems understand a company’s products, expertise and market position.

3. Analyse visibility by market, language and search intent

AI-generated answers can vary between models, countries, languages and prompts. A global visibility score may conceal weaknesses in individual markets or at important stages of the customer journey.

Brands should therefore assess how they appear for different question types, including awareness, product comparison, evaluation and purchase-intent prompts.

Helping Brands Understand Their AI Search Footprint

Pranas AI enables marketing teams to monitor how brands appear across more than 17 AI models from seven providers, including OpenAI, Google, Anthropic, Meta, DeepSeek, xAI and Mistral.

The platform combines brand-mention monitoring, share-of-voice measurement, source intelligence, competitor analysis, brand-perception tracking and content-gap identification. It also provides prioritised recommendations designed to help teams address weaknesses in their AI-search presence.

By analysing visibility at the model, market, language and prompt level, Pranas aims to help organisations understand not only whether AI systems mention their brands, but also how those systems describe them, which sources they trust and where competing brands have stronger coverage.

Study Methodology

The main citation study analysed 20,839 unique prompts that generated Google AI Overviews in August 2026. Following prompt normalisation and deduplication, Pranas recorded 225,094 citations across 13,996 root domains.

The supporting travel study analysed 10,227 prompts to examine the relationship between brand mentions and direct links to owned domains. A separate study of 10,000 smartphone and electronics-related prompts evaluated differences between AI visibility and local market position.

About Pranas

Founded in March 2025, Pranas Platforms Pte. Ltd. is an AI search visibility and brand intelligence company headquartered in Singapore.

The Pranas platform helps brands, agencies and marketing teams understand how they appear across AI-generated answers, identify the sources influencing those answers, compare visibility with competitors and find opportunities to improve discoverability, credibility and attribution.

For more information or to request an AI brand visibility report, visit https://pranas.co/.

Contact Info:
Name: Alex Schulz
Email: Send Email
Organization: Pranas Platforms Pte. Ltd.
Website: https://pranas.co/

Release ID: 89203889

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