AI is changing how people discover, compare, and trust brands. Search is no longer limited to traditional results pages, and brand reputation is no longer shaped only by what audiences see in news coverage, owned channels, or social media.
Increasingly, brands are being summarized, recommended, ranked, and described by AI answer engines — often before a customer, stakeholder, journalist, or decision-maker ever reaches a company website.
That shift was the focus of Agility PR Solutions’ recent webinar, The AI Visibility Gap: New Rules for PR and Brand Reputation in the AI Era, hosted by Pragya Dubey, VP of Global Services at Agility. Drawing on Agility’s proprietary research, the session explored how AI platforms are surfacing brands, which sources they rely on, and why PR teams need to rethink visibility, media strategy, and measurement for an AI-driven landscape.
AI visibility is now a reputation issue
Two of the central questions from the webinar were simple but urgent: Is your brand showing up in AI answers? If yes, is it being represented accurately?
Agility’s research found that PR and communications professionals rated their current AI visibility at 5.5 out of 10, and the accuracy of their brand representation at 5.6 out of 10. In other words, for many teams, AI visibility still feels like a coin toss.
That uncertainty creates a new kind of reputation risk. If AI platforms are already shaping perception, PR teams need a way to understand whether their brand appears, how accurately it is described, which competitors appear alongside it, and what sources are influencing those answers.
PR teams are prioritizing AI visibility, but measurement is still early
The research showed that 46% of PR and communications professionals consider AI visibility a critical or high priority. Meanwhile, 62% monitor their brand across AI platforms at least monthly, with some doing so weekly or daily.
That momentum is encouraging, but manual checking is not enough. AI visibility is not static. Platforms, prompts, citations, sources, and answers can shift quickly.
The takeaway: AI visibility needs to become a repeatable measurement practice, not an occasional spot check. Teams need systems that help them understand whether their brand appears, how prominently it appears, how accurately it is described, and how visibility changes over time.
AI platforms rely on sources PR already influences
Agility analyzed more than 24,000 prompt-and-answer pairs across ChatGPT, Gemini, Perplexity, and Claude, spanning 48 industry sectors. The research surfaced more than 183,000 brand mentions and 177,000 citations.
One of the most important findings: AI answer engines frequently cite sources that PR and communications teams already influence, including corporate websites, newsroom pages, trade media, major media, local and regional outlets, blogs, press releases, and review sites.
Corporate sources accounted for a large share of citations, but, as Pragya emphasized, newsroom content is often part of that picture, making PR-owned content especially important.
The implication is clear: AI visibility is not just an SEO challenge. It is deeply tied to earned media, owned media, media relations, and the credibility signals PR teams help create.
Trade and niche media may matter more than teams realize
Traditional tier-one media still matters, but Agility’s findings suggest that AI platforms do not rely only on mainstream outlets.
Trade publications, local and regional media, blogs, specialist sites, and other niche sources play a meaningful role in the citation ecosystem. That means the most valuable source for AI visibility may not always be the outlet with the largest audience. It may be the outlet with the most relevant and accessible information for a given query.
For PR teams, this creates an opportunity to elevate the role of trade media, expert sources, regional outlets, product-focused reviews, newsroom content, and syndicated press releases as part of a broader AI visibility strategy.
Performance-focused content is becoming more important
Another major takeaway: AI platforms appear to favor content that explains what a brand, product, or service does, not just what the brand stands for.
Agility’s research found that performance-focused content was heavily represented in AI-cited answers. This includes content that explains benefits, features, comparisons, use cases, proof points, outcomes, and reasons a brand may be recommended.
For PR teams, brand storytelling now needs to be supported by clear, evidence-rich content that answers questions like:
- What does the product or service do?
- What problem does it solve?
- How does it work?
- How does it compare to alternatives?
- Why should it be trusted?
In short, PR content now needs to be both compelling for people and useful for AI answer engines.
Press releases may need a new role in the AI era
The webinar also raised an important shift in how PR teams think about press releases.
Traditionally, teams have asked whether an announcement is “newsworthy” enough to issue broadly. But in an AI-driven discovery environment, press releases can also help make structured, factual, brand-owned information available across the open web.
That does not mean overloading every release. It means thinking more intentionally about what information AI platforms need in order to accurately understand and represent the brand.
Clear product descriptions, proof points, use cases, category context, differentiators, and links to authoritative owned content can all help strengthen how a brand is interpreted by AI engines.
AI visibility strategy must be sector-specific
Agility’s research covered 48 sectors, and the webinar emphasized that AI visibility does not look the same across every industry.
Different categories surface different numbers of brands. Different industries rely on different citation sources. Some sectors may be more competitive, while others may have fewer brands appearing in AI-generated answers.
That means PR teams need to understand which AI platforms matter most for their audience, which prompts are most relevant to their category, which competitors are appearing, and which sources are being cited.
The strongest AI visibility strategies will combine platform-specific insight with sector-specific media and content planning.
Earned media is becoming even more strategically valuable
During the Q&A, Pragya emphasized that earned media matters because AI engines look for signals of credibility, originality, and consistency. Third-party validation gives AI platforms more confidence than brand claims alone.
This reinforces PR’s strategic role. Earned media has always helped build trust with human audiences. Now, it may also help shape how machines understand and recommend brands.
For PR teams, this creates a new measurement opportunity: tracking whether specific articles, outlets, or sources are being cited in AI-generated answers over time.
The bottom line
AI visibility is quickly becoming a new layer of brand reputation. PR teams can no longer assume that visibility in search, earned media, or owned channels automatically translates into visibility across AI answer engines.
The opportunity is significant. Many of the sources shaping AI answers — earned media, trade coverage, newsroom content, press releases, and credible third-party validation — are already within PR’s sphere of influence.
But influence starts with measurement.
To close the AI visibility gap, teams need to understand where they stand today, which sources are shaping their presence, and what actions will help their brand show up more accurately, credibly, and consistently in the AI-driven discovery journey.
Watch the full webinar here to hear Pragya Dubey walk through the findings and recommendations in more detail.
For a deeper look at the research, download Agility’s full report, Closing the AI Visibility Gap in 2026, which explores how AI answer engines discover, surface, and recommend brands across today’s evolving search landscape.
