Reputation is the new optimization: why PR is the key to AI search visibility

Something significant shifted when ChatGPT crossed 100 million users in early 2023. Marketers and communications professionals who had spent years perfecting their SEO playbooks suddenly found themselves asking a new question: what happens when people stop searching Google and start asking AI?

AI-powered search tools do not index pages the way traditional search engines do. They synthesize information from across the web, drawing heavily on sources they deem credible: trade publications, analyst reports, earned media coverage and third-party expert commentary. In other words, they rely on the same signals that PR professionals have been building for decades.

This convergence has given rise to Generative Engine Optimization, or GEO—a discipline focused on ensuring your brand appears accurately and favorably in AI-generated responses. And while the technical dimensions of GEO have attracted attention, the strategic core of it is fundamentally a communications challenge.

To understand why PR matters for AI visibility, it helps to understand how large language models (LLMs) are trained. These systems learn from vast corpora of text data—much of it drawn from high-authority sources like news outlets, industry publications, academic journals and widely cited reports. Owned content, such as company websites and blog posts, represents a relatively small and often lower-weighted slice of that data.

This is a structural shift in how brand authority is established and recognized. Traditional SEO rewarded technical precision—keyword density, page speed, backlink profiles. GEO rewards something harder to manufacture: genuine third-party credibility. Earned media placements, executive commentary in trade publications, inclusion in industry rankings and citations in analyst reports are the currency of AI visibility.

This creates both an opportunity and a challenge. Organizations with strong thought leadership programs and active media relations strategies are already accumulating the signals that LLMs value. Those that have depended primarily on owned channels such as websites, social media and email campaigns may find their brands underrepresented or misrepresented in AI-generated responses.

How communications teams are positioned to lead GEO strategy

The emergence of GEO has introduced a new question in many organizations: who owns it? According to Muck Rack's 2026 State of PR report, 29% of PR professionals say no one owns GEO at their organization. Communications teams are well positioned to fill it. PR professionals understand the media landscape, have established relationships with journalists and analysts, and they are practiced at crafting narratives that resonate with external audiences. These capabilities translate directly into the work required for AI visibility.

Executive thought leadership is a particularly high-leverage activity in this context. When senior leaders publish bylined articles in trade publications, speak at industry conferences or contribute expert commentary to news stories, those appearances generate exactly the kind of authoritative, third-party signals that AI platforms prioritize.

For communications teams looking to lead GEO strategy, the practical work involves identifying the publications, platforms and content formats that LLMs frequently cite in your sector, then systematically placing your organization's voices and perspectives in those channels.

The most effective organizations approach this as a cross-functional challenge. Marketing teams manage technical infrastructure and owned content. Communications teams build the external credibility signals such as earned media, expert citations and analyst relationships that give AI systems reasons to trust and reference the brand.

However, simply generating media coverage is not sufficient for AI visibility. The placement, the source and the consistency of messaging all matter. AI systems are not neutral aggregators. They draw on specific publication categories, weight certain source types more heavily than others and can perpetuate inaccuracies if a brand's messaging is inconsistent or if third-party coverage contains errors.

This means communications teams must be proactive, not just reactive. Monitoring how your brand is represented within LLMs is becoming a standard part of reputation management. Identifying where AI platforms are pulling inaccurate or incomplete information about your organization and then generating corrective coverage in high-authority sources is a new discipline that sits squarely within the PR function.

There is also a strategic targeting dimension to this work. Not all earned media placements are equally valuable from a GEO perspective. Coverage in the publications that LLMs are most likely to have indexed and weighted like major trade publications, widely syndicated news outlets and frequently cited research reports carries more AI visibility value than placements in lower-authority channels.

The practical implications of GEO are significant for how PR professionals define their function. For decades, the core value proposition of communications work was influencing what people think. Media placements shaped perception. Reputation was measured in column inches and audience reach.

The discipline is now evolving toward something more fundamental: influencing what AI systems know. This is not a departure from PR's core expertise but an extension of it. The skills that make communications professionals effective like building relationships with credible sources, placing authoritative voices in relevant channels and maintaining consistent, accurate messaging across multiple platforms are precisely the skills that GEO requires.

What changes is the urgency and the audience. AI systems are trained continuously. The coverage your organization generates today is shaping the responses that AI platforms will deliver to your potential clients, project partners and industry peers for months or years to come.

Navigating the intersection of PR and GEO requires both strategic clarity and communications expertise. AOE's PR professionals know AI and can help you build the credibility signals that matter. For a deeper look at how AI is transforming the PR function, read our related post: The impact of AI on public relations: a PR playbook overhaul. If you would like a plan that is personalized to you, contact AOE to speak with a member of our PR team.

Frequently asked questions

What is Generative Engine Optimization (GEO)?

Generative Engine Optimization is the practice of ensuring a brand appears accurately and favorably in AI-generated search responses from platforms like ChatGPT, Perplexity and Google's Gemini. Unlike traditional SEO, which focuses on ranking web pages in search results, GEO focuses on building the third-party credibility signals—earned media, analyst citations and expert commentary—that large language models use to synthesize information about a brand.

Why do LLMs prioritize earned media over owned content?

Large language models are trained on data drawn from high-authority external sources, including trade publications, news outlets and academic journals. Owned content like company websites represents a relatively small and lower-weighted portion of that training data. As a result, third-party coverage in credible publications carries more influence over how an AI system describes or recommends a brand than the brand's own web content.

Who should own GEO strategy within a marketing or communications team?

According to Muck Rack's 2026 State of PR report, 29% of PR professionals report that no one owns GEO at their organization. While GEO requires cross-functional collaboration between PR and marketing, communications teams are best positioned to lead the strategy. PR professionals have the media relationships, narrative expertise and external credibility-building skills that GEO demands.

How can AEC firms start building AI visibility through PR?

AEC firms should begin by auditing how their brand appears in major AI platforms, then identifying which high-authority trade publications—such as ENR, Architectural Record and Building Design and Construction—are frequently cited in AI-generated responses within their sector. From there, prioritizing executive thought leadership, bylined articles and expert media commentary in those outlets will generate the credibility signals that LLMs are most likely to reference.

Is traditional SEO still relevant in the age of AI search?

Yes. Technical SEO and PR serve complementary functions. SEO ensures owned content is discoverable; PR builds the external credibility that determines what AI systems say about your brand. An effective AI visibility strategy requires both—and the two disciplines are most powerful when marketing and communications teams operate in alignment.

How do you monitor and correct inaccurate AI-generated information about your brand?

Tools like Meltwater's GenAI Lens are designed to monitor how brands are represented within large language models and detect potential misinformation before it spreads. When inaccuracies are identified, the most effective correction strategy is generating authoritative coverage in high-weight publications that clearly establishes the accurate information, giving AI systems a credible source to draw from.