Over the past year, one thing has become clear: AI visibility is one of the biggest topics on the minds of our clients and prospects.
The questions keep coming. What exactly is AI visibility? How is it different from SEO? Does PR actually influence AI visibility? How do you measure it? Where do owned, earned, and shared media fit in?
The reality is we’re all building the plane as we fly it. AI search is evolving quickly, best practices are changing by the month, and there’s no single playbook with all the answers.
To understand what our clients wanted to know most, I turned to our AI-powered call notes, using its chat functionality to analyze hundreds of client conversations and identify the questions that come up again and again. Then, I took those questions to three of PAN’s leading AI visibility experts for their perspectives.
The result is this FAQ: a practical guide to the questions B2B marketing and communications leaders are asking most often about AI visibility. It covers how AI visibility works, how PR influences AI search, the difference between SEO and GEO, how AI systems choose which brands to cite, and how to measure AI visibility over time.
These are the questions we’re hearing every day, and our best answers (as of June 2026).
For a few baseline fundamentals, we turned to Zareen Fidlon, EVP, Head of Integrated Marketing & AI Innovation at PAN, to get us started.
What is AI visibility?
AI visibility is the extent to which a brand appears, is accurately represented, and is cited as a trusted source within AI-generated responses.
AI visibility is about whether AI systems recognize your brand as a credible authority and surface it when buyers use AI to research topics, vendors, and solutions. It encompasses brand mentions, citations where platforms provide them, sentiment and share of voice within AI-generated responses, including whether you show up in response to non-branded questions.
It’s not driven by any single channel, but the result of the authority signals a brand builds across owned, earned, and shared channels. AI systems increasingly use those signals to determine what information is trustworthy enough to surface and recommend.
Key takeaway: AI visibility is about becoming a trusted source AI systems choose to reference.
Why should B2B brands care about AI visibility?
B2B buyers increasingly start their research with AI.
Instead of searching and clicking through results, they ask ChatGPT, Gemini, Claude, or Perplexity to explain a category, compare options, or recommend vendors, and they form an early shortlist before they visit a website or talk to sales. That changes where decisions get shaped. If AI doesn’t surface your brand, or surfaces it inaccurately, you can be filtered out of consideration without ever knowing you were in the running.
AI systems determine what to trust based on authority signals such as third-party validation, citations, recognized expertise, and consistent messaging. Those signals are earned over time through PR, thought leadership, and a strong presence across owned, earned, and shared channels. That’s why AI visibility isn’t a standalone tactic; it’s the outcome of building authority and credibility consistently across channels. As AI becomes the first layer of discovery, the brands that show up as trusted authorities are increasingly the ones buyers consider.
Key takeaway: If AI doesn’t surface your brand during the research process, you may never make it onto a buyer’s shortlist.
To dig into the PR specific questions, Kim Jefferson, SVP of Client Relations at PANBlast, weighed in.
Will a PR investment improve AI visibility?
Yes. Over time, PR helps strengthen the authority signals AI models use to determine which brands to cite, recommend, and trust.
B2B buyers and investors are using AI search to surface companies that meet highly specific criteria. In this new landscape, PR acts as a cog in the credibility ecosystem that feeds these AI models.
First, to help brands improve AI visibility, PR teams need to understand the prompts they’re trying to show up for, then the domains, URLs, and content structures/types being cited for those prompts. Then, PR needs to partner with marketing and customer success to create, place, and optimize the types of content needed to improve visibility.
Key takeaway: PR alone won’t drive AI visibility, but it’s a critical part of the credibility ecosystem that influences AI-generated answers.
How can brands get cited by AI more often?
Brands improve their chances of being cited by publishing clear, factual, authoritative content across owned, earned, and shared channels.
For PR teams, getting brands cited by AI requires a shift from storytelling to ruthless clarity and simplicity. When distributing press releases, for example, if AI visibility is the main goal, start by isolating a single factual AI hook, like “PANBlast launched AI visibility services for B2B tech and AI brands.” Next, draft a pun-free headline under 100 characters, an inverted-pyramid lead under 100 words, an immediate FAQ or quick facts bulleted list and question-based subheads every 150–200 words, ensuring statistics are listed, URLs are typed out, and an FAQ section sits above the boilerplate.
Marketing and comms teams need to partner on the other types of content most likely to be cited by AI, including listicles, G2 reviews, Reddit threads, and YouTube videos.
Key takeaway: AI rewards brands that consistently create trustworthy, easy-to-understand content.
What types of content are most likely to be cited by AI?
AI frequently cites a mix of user-generated content, trusted media outlets, company-owned content, and third-party review platforms.
AI visibility software Peec.ai analyzed 30 million sources across ChatGPT, Google AI Mode, Gemini, Perplexity, and AI Overviews in the US and found the top 10 cited sources are a mix of user-generated content (Reddit, YouTube, LinkedIn, Medium), media sites (Forbes, TechRadar) and review sites (G2, Yelp). PR teams have a place in each of these sectors, but it may be a step beyond what brands typically think of as PR.
User-Generated Content (LinkedIn, YouTube, Reddit):
- LinkedIn Thought Leadership: Long-form, ungated articles from company thought leaders are highly crawled and frequently cited by AI, so PR teams should weave these into campaign strategies.
- YouTube: As the undisputed No. 1 podcast platform, securing podcast interviews and engaging with video influencers on YouTube is a massive driver of AI search visibility.
- Reddit: While PR pros can’t directly engage without being flagged, monitoring Reddit conversations allows teams to alert internal brand experts to jump in with genuine, meaningful feedback on trending topics.
Media & Corporate Sites (Forbes, TechRadar, blogs):
- Forbes Council Profiles: PR teams seeing Forbes in AI visibility dashboards should advise client thought leaders to secure a profile with a Forbes Council.
- Media Relations: The definition of a “media outlet” is widening. Beyond securing placements on traditional media sites like Forbes or TechRadar, your corporate blog can also serve as an earned channel. By leveraging tactics like blog swapping and publishing original, proprietary data, your site becomes a publication and a direct source for AI.
Third-Party Review Sites (G2, Yelp):
- Review Management: Because AI models heavily rely on structured review platforms to answer “best of” and comparative commercial prompts, PR teams should partner with customer success leaders to manage brand presence, driving fresh customer reviews and optimizing profiles on sites like G2.
Key takeaway: The strongest AI visibility strategies extend well beyond traditional media relations.
How should companies change their PR strategy for the AI era?
Modern PR strategies should build credibility with both human audiences and AI systems by expanding beyond traditional media into the channels AI frequently references.
Comms and marketing leaders need to stop maniacally focusing on top-tier national business media. Splashy WSJ or NYT pieces are great for investor/enterprise buyer credibility (and making CEOs and boards happy), but many of those major outlets are behind paywalls or actively embroiled in lawsuits with LLM creators. If AI visibility is your north star, those gated walls mean bots can’t even crawl the coverage.
In the AI era, your PR strategy needs to be dual-targeted: built for LLMs AND humans. Right now, top-tier media hits really only speak to the latter. To improve AI visibility, companies need to shift their energy toward the sources that specifically contribute to their target prompt visibility. We see the following tactics currently working for AI visibility across our client base.
- Targeting more non-traditional (Medium, YouTube, etc.), niche trade, and media cited for target prompts.
- Building robust LinkedIn content programs.
- Investing in community building where organic conversations happen.
- Creating AI-friendly owned content and pursuing co-marketing with other companies’ corporate blogs.
Key takeaway: The future of PR is creating content that serves both humans and LLMs.
Is earned media a worthwhile investment if it is not sourced by LLMs?
Absolutely. Earned media builds credibility with buyers, investors, analysts, and journalists, even when AI doesn’t directly cite it.
Your PR strategy should not be singularly focused on LLM visibility. Abandoning humans as the ultimate consumers of your content would be a mistake. Write for humans, optimize for AI, and continue to monitor what is moving the needle with your actual buyers. Not just bots.
Key takeaway: Optimize your PR program for AI without losing sight of the humans ultimately making purchasing decisions.
And for insight on the intersection of measurement, owned content and AI viz, we asked Katie Weedman, Senior Content Strategist at PAN, the following questions.
What should we measure to know if our AI visibility is improving?
Measure AI visibility using both business outcomes and visibility metrics.
On the business impact side, measure AI assistant referral traffic in GA4, downstream engagement from those visits, conversions, assisted pipeline, and form fills where users self-report AI tools as part of their discovery journey.
Then supplement that with AI visibility intelligence: brand mentions, source citations, share of answer/voice, competitor presence, sentiment, and the quality or accuracy of how your brand is described.
The goal is to understand whether your brand is becoming more discoverable, more accurately represented, and more useful to the audiences turning to AI search for answers.
Key takeaway: No single metric tells the whole story. Focus on trends across visibility, engagement, and business impact.
How do we optimize our website for AI search?
Build a technically sound website, then publish clear, authoritative content that directly answers the questions your audience is asking.
Begin with strong SEO fundamentals: crawlable pages, clear site structure, fast performance, clean metadata, schema markup, internal linking, and authoritative content.
Then optimize for how AI systems retrieve and synthesize information. Publish content that directly answers the questions your audience is asking, with clear explanations, consistent brand and product facts, data-backed proof points, and useful context around the problem, solution, and outcome.
A helpful framework is: problem → solution → evidence → next step. The goal is to make your website easy for both people and AI systems to understand, retrieve, trust, and cite.
Key takeaway: Websites optimized for people are increasingly the same websites AI systems find easiest to retrieve and cite.
How long does it take to improve AI visibility?
AI visibility typically improves over time as your authority grows, though timelines vary based on your existing authority, content quality, crawlability, brand consistency, third-party coverage, citation sources, competitive landscape, and how quickly AI systems refresh or retrieve information.
Some improvements, such as a cleaner website structure, stronger answer-ready content, and corrected brand facts, can create early signals within weeks. Broader visibility gains across AI answers, citations, and competitive presence often take longer because they depend on source discovery, reinforcement across the web, and repeated retrieval over time.
A “4–6 week” estimate may be possible in some cases, but it should be treated as a rough directional benchmark, not a guarantee.
Key takeaway: AI visibility is built through consistent credibility, not quick wins.
AI visibility glossary
- AI visibility: The likelihood that an AI assistant mentions, accurately describes, or recommends your brand when responding to relevant user prompts.
- AI citation: A source referenced by an AI assistant to support or generate an answer.
- AI referral traffic: Website visitors who arrive from AI assistants such as ChatGPT, Gemini, Claude, or Perplexity.
- Authority signals: Evidence that helps AI systems determine whether a source is trustworthy, such as earned media, expert content, reviews, and citations.
- Earned media: Editorial coverage secured through media relations rather than paid advertising.
- GEO (Generative Engine Optimization): The practice of creating and structuring content so generative AI systems can easily retrieve, understand, and reference it.
- Hallucination: An AI-generated response that presents inaccurate, fabricated, or misleading information as factual.
- LLM (Large Language Model): An AI model trained on vast amounts of text to understand language and generate human-like responses.
- Owned media: Content a brand controls directly, including its website, blog, resource center, and newsletter.
- PR (Public Relations): The practice of building awareness, credibility, and trust through earned media, thought leadership, executive visibility, and reputation management.
- Prompt: The question or instruction a user gives an AI assistant.
- Retrieval: The process AI systems use to locate relevant information before generating a response.
- SEO (Search Engine Optimization): The practice of improving a website’s visibility in traditional search engine results through technical optimization, content, and authority building.
- Share of answer: The percentage of AI-generated responses in which a brand appears compared to competitors for a defined set of prompts.
- Share of voice: A measurement of how frequently a brand is mentioned in media compared to competitors.
- Third-party validation: Independent recognition of a brand through media coverage, analyst reports, customer reviews, awards, or industry rankings.
- Thought leadership: Original insights, expertise, and perspectives shared by subject matter experts to build authority and influence within an industry.
Key insights from this FAQ on AI visibility:
- AI visibility is the result of credibility, not a single marketing tactic. Brands improve AI visibility by building authority across owned, earned, and shared media.
- PR plays a critical role because it creates the third-party validation AI systems use to evaluate trust. It’s one piece of a broader credibility ecosystem.
- Content built for both humans and AI performs best. Clear, factual ,and authoritative content is more likely to be understood, cited, and recommended.
- Measurement should go beyond rankings. Track AI mentions, citations, share of answer, referral traffic, and business outcomes together to understand your progress.
- The AI landscape is evolving quickly. Continue testing, monitoring, and adapting your strategy as AI search and buyer behavior change.
Have a question we missed? We’d love to hear it. Message me on LinkedIn, and I’ll add it to this list.