As AI-generated search experiences become a more prominent part of how people discover information, organizations face a new challenge: understanding how they are represented when Agentic systems discuss their Brand, products and areas of expertise.
For years, marketers have relied on Search Engine Ranking Places (SERPs), traffic data and media monitoring to evaluate their visibility online. While these metrics remain important, they only tell part of the story. Increasingly, potential customers are turning to platforms such as ChatGPT, Gemini and Claude to answer questions, compare suppliers and research solutions, in fact 52% of U.S. adults now use large language models according to research from Elon University. In these LLM environments, visibility is not determined solely by where a website ranks, but by whether a Brand is included in the answer itself.
This creates a new strategic requirement for PR and marketing teams. Before influencing AI-generated recommendations, organizations first need to understand how they currently appear within them.
An AI visibility audit provides that foundation.
Why Traditional Monitoring Is No Longer Enough
Most organizations already have processes for tracking media coverage, backlinks and Brand mentions. These remain valuable indicators for PR performance, but they do not necessarily reveal how AI systems interpret a business. This is where understanding how AI is interpreting your brand matters just as much as understanding where your brand is being mentioned.
A Brand may secure regular media coverage on publications such as Forbes or The New York Times and still fail to appear when users ask AI platforms relevant category questions. Equally, an organization may find that LLMs describe it in ways that do not align with its positioning, messaging or commercial priorities, because AI systems draw on a much broader set of sources than a Brand’s own content and recent media coverage.
The challenge is that AI systems do not simply reproduce information: they synthesize it. And in doing so, they create their own interpretation of Brands, industries and topics based on the information available. Understanding that interpretation should be the starting point for any AI visibility strategy.
What Is an AI Visibility Audit?
At its heart an audit should be a structured assessment of how AI systems represent a Brand across a range of relevant topics, prompts and buying-stage queries – to understand how visible the brand is in the responses. Rather than focusing on rankings alone, the objective is to understand the narratives, associations and sources that influence Agentic responses.
At its simplest, the process involves asking questions such as:
- How do AI systems describe our organization?
- What topics are we associated with?
- Which competitors are surfaced instead of us?
- Which sources influence those recommendations?
- Are Agents presenting accurate information?
The answers can reveal opportunities that would be difficult to identify through traditional media monitoring alone.
Brand Representation: What Is AI Saying About You?
The first step in any audit is understanding how AI systems describe your organization. This may sound straightforward but the results can often be surprising. Many businesses invest significant resources in defining their positioning, messaging and differentiators. However, LLMs build their understanding from a wide range of sources and may not always reinforce the messages your Brand wants to own.
Some website owners discover that important capabilities are rarely mentioned. Others, that AI systems focus heavily on legacy products, outdated positioning or secondary areas of expertise. The objective is not simply to measure visibility but to assess whether that visibility aligns with your business goals.
If a Brand wants to be known for sustainability, innovation or specialist expertise, those themes should be consistently reflected in AI-generated responses. Where they are absent, there may be a visibility gap that Digital PR activity can help to address. This ties into topic ownership, you need to own the topics you want AI to connect you with.
Topic Ownership: Which Conversations Do You Own?
LLMs increasingly understand organizations through associations. Rather than viewing a business as a collection of URLs, they attempt to understand what that organization does, who it serves and which topics it is most closely connected with.
This makes topic ownership a critical component of any AI visibility audit. Brands should assess which themes they appear to own, which conversations are being led by competitors and where important visibility gaps exist.
For example, an online casino brand may want to be associated with topics such as online casino bonuses, mobile gaming, live dealer experiences, casino rewards and responsible gambling. However, an audit may reveal that AI systems more frequently associate those topics with competitors, despite the brand investing heavily in those areas.
This does not necessarily indicate a product or service issue. More often, it reflects a visibility challenge.
A practical audit might review 50 AI-generated responses across ChatGPT, Gemini and Claude for a topic such as “responsible gambling”. The findings may show:
- Competitor A mentioned in 34 responses
- Competitor B mentioned in 22 responses
- The audited brand mentioned in 6 responses
This would indicate a topic ownership gap. The brand may have relevant expertise, products or initiatives, but AI systems are not consistently associating it with that conversation.
Organizations that appear most frequently in AI-generated answers are often those that have repeatedly reinforced their expertise through thought leadership, research, commentary and earned media. For instance, if users ask:
- “What makes an online casino trustworthy?”
- “What should I look for in a sportsbook app?”
- “How do casino rewards programmes work?”
Brands that have consistently contributed expert commentary, published research or earned media coverage around those topics are more likely to be referenced, associated or recommended.
Understanding which topics AI associates with a brand provides a valuable benchmark for future PR activity. It helps identify where a brand already has authority, where competitors are dominating the conversation and where future campaigns, commentary or research could help strengthen brand-topic associations.
Understanding What Shapes AI Answers
One of the most useful outcomes of any audit is identifying the sources that influence AI-generated responses. Every recommendation, description and comparison is shaped by information from somewhere. In many cases, certain publications, websites or specialist resources appear repeatedly across AI-generated answers. Understanding these sources can help organizations refine their media strategies.
Traditionally, media targeting has focused on reaching the right audience through respected publications. While this remains important, AI search introduces another consideration: identifying the sources that influence AI-generated answers.
The publications shaping AI responses may not always be the largest or most prestigious. In some sectors, specialist industry titles, research organizations and niche resources can have a disproportionate influence on how Agents understand a category.
For PR professionals, this insight can help inform future targeting and thought leadership activity.
Benchmarking Competitors
Understanding your own visibility is only part of the picture. A comprehensive audit should also examine how competitors appear across the same prompts and topics.
- Which Brands are recommended most frequently?
- Which organizations dominate commercially valuable conversations?
- Which competitors appear strongly associated with topics that your brand would like to own?
Benchmarking provides important context. Without it, it is difficult to determine whether visibility challenges are unique to a brand or part of a broader market pattern.
Competitor analysis can also uncover opportunities. If rival organizations are weakly represented within certain areas of a category, there may be an opportunity to establish ownership before the market becomes more competitive.
Fact-Checking AI Responses
Despite rapid improvements, AI systems are not always accurate. Responses can sometimes be influenced by outdated articles, historical coverage or inaccurate third-party information or even adding 2+2 and getting 5 – so-called “hallucination” where outwardly similar bits of information are cross referenced inappropriately. For Brands, this presents both a reputational and commercial risk. For instance, pulling an incorrect email for your customer service or claiming a product has been discontinued when it hasn’t.
Any visibility audit should therefore include a review of factual accuracy. Organizations should assess whether descriptions remain current, whether key information is represented correctly and whether outdated narratives continue to appear.
Identifying and working to address these issues early creates an opportunity to strengthen messaging and reinforce more accurate representations through future PR activity.
Turning Insights Into Action
Collecting information is only useful if it leads to action. One of the most effective ways to prioritise findings is through a SWOT analysis. Strengths highlight the areas where a brand already performs well within AI-generated responses. These may include strong topic ownership, consistent recommendations or visibility across key prompts.
Weaknesses often reveal gaps in visibility, inconsistent messaging or limited associations with strategically important topics. Opportunities frequently emerge through competitor analysis, highlighting conversations, themes or sources where stronger representation could be achieved.
Threats may include competitors strengthening their position, outdated information influencing responses or third-party sources shaping perception in undesirable ways. This framework helps transform observations into a practical roadmap for future activity.
Keep Going
AI visibility is not a one-off exercise, it should be part of your quarterly reporting. The sources influencing AI-generated answers continue to evolve. Competitors launch campaigns, new content enters the ecosystem and AI models adapt to changing information landscapes. As a result, visibility can change over time.
Organizations that monitor their representation regularly are better positioned to identify emerging risks, strengthen topic ownership and respond to competitive threats.
For most brands, a quarterly review provides a practical balance between maintaining oversight and generating meaningful strategic insight.
The Foundation of an AI Visibility Strategy
Before organizations can influence how AI systems represent them, they need a clear understanding of their current position. An AI visibility audit provides that baseline. By examining Brand representation, topic ownership, source influence, competitor visibility and factual accuracy, organizations can develop a more complete understanding of how they appear within AI-generated search experiences.
The Brands that succeed in AI search are unlikely to do so by accident. They will be the organizations that understand how they are perceived, identify the narratives they want to own and consistently reinforce those associations over time.
An audit is where that process begins.
For more information about getting your website visibility audit underway, get in touch.
