For our 2026 research report, Closing the AI Visibility Gap, Agility PR Solutions analyzed 24,480 prompt-and-answer pairs across ChatGPT, Perplexity, Gemini, and Claude, capturing 183,004 brand mentions and 177,487 citations across 48 industries. The aim was to analyze major AI answer engines and understand the mechanics behind some key questions:
- How many brands are mentioned in an AI answer?
- What is the driving factor behind those brand recommendations?
- What are the sources (citations) that AI engines extract information from?
A few patterns stand out, and together they reshape how communications teams should think about AI visibility. Here are four key takeaways from the data research:
4 Key Takeaways from Agility’s ‘Closing the AI Visibility Gap’ Report
Here are four key patterns we analyzed from Agility’s data research:
Every AI answer is a shortlist, and most brands are not on it
AI engines named an average of 7.5 brands per answer. Compared to conventional SERPs that show a list of 20 results, this is a very limited space. Effectively, every prompt is a closed, competitive list, and brands that miss the cut are entirely absent from the conversation.
What this means for PR teams: The strategic focus shifts from keywords and SERP rankings to consistent inclusion across brand mentions for the specific prompts your audience asks for. Start by mapping out a list of prompts that matter and measuring your visibility across AI platforms relevant to your business.
Earned media is the deciding factor
The report makes it clear that AEO remains a citation-driven strategy, as all LLM platforms offer at least one citation for at least 94% of the responses. Industry research confirms the finding: earned media and third-party content are highly influential in increasing AI visibility and establishing niche authority.
What this means for PR teams: Effective media outreach and third-party coverage are quickly becoming the primary AI-visibility levers. PR teams need to realign their focus on outlets that are moving the needle across both your industry and the AI platforms preferred by your audience.
Performance is what gets content cited
Across all four engines and all 48 categories, performance drove roughly 79% of recommendations, meaning engines cited evidence of what a product does and how well it does it. Demonstrable outcomes beat familiarity, so the content most likely to gain citations is likely to be evidence-backed, such as benchmark data, case studies, and third-party performance validation.
What this means for PR teams: PR teams need to create content centred around quantifiable proof. Pairing brand narrative with measurable outcomes drives user trust and helps AI visibility. Once you start creating performance-focused content, monitor the shift in narrative across AI engines to see how accurately your brand is being portrayed.
AI visibility is not one size fits all across engines
The four engines behave like distinct channels. Gemini surfaced the most brands per answer, giving it the highest brand density. Claude cited the most sources, averaging 12.8 per answer, roughly 3.5 times ChatGPT’s count. Perplexity included citations most consistently and leaned most heavily on corporate content, while ChatGPT drew most heavily on major media and was most likely to answer without a citation. The same earned-media footprint can produce very different results depending on where an audience asks.
What this means for PR teams: It is crucial to identify what AI engines your audience relies on to monitor and benchmark performance. And since every engine extracts information differently, this information is crucial in guiding your content strategy and how you interpret the share of voice and visibility metrics.
Visibility Intelligence: How Agility can help measure PR performance
The data describes an evolving landscape where visibility is scarcer, more evidence-driven, and more fragmented than what PR teams are used to. The new course of action requires consistent measurement, ongoing AI visibility audits, and an evolving strategy that changes with the algorithm.
Conventional tools are not built to capture this data. PR teams require purpose-built measurement tools to identify their current AI visibility landscape and build on it.
Agility’s Visibility Intelligence offers a structured, real-time view of how your brand surfaces across ChatGPT, Claude, Gemini, and Perplexity. Instead of manually querying each AI engine, Visibility Intelligence runs prompts against major AI platforms to determine visibility, how accurate it is relative to the intended messaging, which sources are driving the strongest influence, and how your brand compares to its competitors. Users can turn that intelligence into targeted media outreach to further boost their earned media citations, without even leaving the platform.
The brands that hold their place in AI answers will be the ones treating earned media as a performance channel, backing their narrative with citable proof, and tailoring their approach engine by engine. For a deeper look into what affects AI visibility, including the industry-level breakdowns, see Agility’s Closing the AI Visibility Gap report.
