AI visibility strategies: How to appear in AI search results and LLMs

Your brand could have the best content, the strongest reputation, and a loyal customer base – but if AI tools like ChatGPT and Google’s AI Overviews can’t find you, recommend you, or represent you accurately, you’re invisible where it matters most. Congratulations – you’ve been ghosted by a robot.

Welcome to the era of AI visibility, where being discoverable is about more than simply ranking on Google.

What is AI visibility?

AI visibility is how discoverable, recognisable, and accurately represented your brand is within AI-powered search tools and large language models (LLMs). When someone asks ChatGPT, Perplexity, or Google’s AI Mode a question related to your industry, AI visibility determines whether your brand appears in the answer – and how it’s portrayed.

Think of it like being at a party: if the AI doesn’t know who you are, it’s not introducing you to anyone.

It’s known by many different names and acronyms, including Answer Engine Optimisation (AEO) and Generative Engine Optimisation (GEO), but to keep things simple, we’ll keep referring to it as ‘AI visibility’.

Unlike traditional Search Engine Optimisation (SEO), which focuses on ranking in search engine results pages, AI visibility depends on how well AI systems can understand and represent your brand across the entire digital landscape.

That includes your website, media coverage, social presence, customer reviews, and any other place your brand shows up online.

If the information is clear, consistent, and credible, AI tools can surface your brand confidently.

If it’s fragmented or absent, you risk being left out of the conversation entirely.

SEO vs. GEO: the key differences

It’s important to note that most SEO best practices still apply in GEO – the line is blurred.

Nonetheless, there are a few key differences to point out. Here’s a quick table which summarises them:

Why is AI visibility important?

AI is fundamentally changing how buyers research, evaluate, and choose solutions. Instead of clicking through search results, they’re getting direct, synthesised answers from LLMs that pull information from across the web.

For brands, this shift brings both risks and opportunities, and understanding the implications is essential for staying competitive.

Here are five of the biggest developments we’ve seen so far.

1. Traditional search traffic is shrinking

Even if your audience still uses Google, the search engine results page (SERP) is getting messier and more complex. AI Overviews now trigger for more queries (some estimates say over half of all searches), pushing traditional organic listings further down. Google Ads, SERP features, and the new AI Mode all compete for attention.

AI-powered search tools like ChatGPT and Perplexity do a similar job, synthesising information from multiple sources and delivering direct answers without requiring users to click through to any website.

This means fewer site visits, even if your content informed the AI’s response.

The answers users receive are inherently personalised and context-sensitive, shaped by their language choices, search intent, search history and logged-in accounts, making it even harder to predict or measure how your brand will be represented.

While AI-driven search referrals currently account for just 1% of website traffic, projections from Semrush suggest overall organic traffic could drop by more than 50% by 2028.

As a result, brands need to shift focus from traffic volume to traffic quality, and diversify their presence across channels like social media, PR, and video, not just their own website.

2. Brands without authority are becoming invisible

Digital brand authority isn’t a new concept. SEO professionals have been talking about Domain Authority, digital PR, and link building for years.

What’s changed is that AI tools now rely on these same signals to decide which brands are credible and worth recommending. If your brand lacks authority or recognition across the digital landscape, you risk being left out of AI-generated answers entirely.

In other words, AI kills weak brands.

Building authority means being mentioned, talked about, and recommended in the right spaces. That includes industry publications, analyst reports, LinkedIn activity, media coverage, customer reviews, and expert commentary. Link building is another tactic which still matters, but it’s not enough on its own.

Quality also matters more than quantity here. It might be that a handful of niche websites or platforms carry weight in your industry:

• A SaaS brand might need more mentions in analyst reports and software review sites.
• A personal finance brand might need validation from top social media influencers or national newspaper journalists.
• An educational institution might gain its credibility through award nominations and ranking tables.

The exact mix varies, but the principle is the same: everything you do across PR, SEO, and social contributes to how AI understands and represents your brand.

3. Tick-box SEO content no longer guarantees success

Traditional SEO content isn’t dead – it’s been continuously evolving. Google has used natural language processing (NLP) to understand search intent since updates like Hummingbird and BERT, moving away from simple keyword matching towards semantic understanding.

But LLMs take this a step further, interpreting context and nuance at a level that makes generic, tick-box content increasingly ineffective.

When people ask AI tools complex, conversational questions like “What’s the best CRM for a mid-sized SaaS company with a small remote sales team?”, generic, keyword-stuffed content won’t cut it.

Instead, LLMs prioritise content that:

• Demonstrates genuine expertise and original thinking
• Addresses specific questions or pain points in a natural, conversational way
• Provides unique insights, not rehashed industry talking points
• Is structured clearly so AI can easily parse and summarise it

Surface-level blog posts that repeat what everyone else is saying will struggle to gain traction.

Depth, originality, and expertise are what separate content that gets surfaced by AI from content that gets ignored. That applies to your choice of format, too. Got an idea for a new blog post? Would it deliver better engagement as a YouTube video? Or an infographic?

The future of search isn’t just AI-driven, it’s multimodal.

Most importantly, create content for humans first, not algorithms or machines – and you won’t go too far wrong.

4. AI can be a brand reputation risk if not influenced proactively

AI tools pull information from anywhere your brand appears online. If that information is inconsistent, outdated, or incomplete, AI can easily misrepresent you or, worse, ignore you entirely.

The challenge is that AI doesn’t fact-check or prioritise accuracy the way a journalist might. It synthesises patterns from what’s available, which means outdated press releases, conflicting product descriptions, or incorrect details can all feed into how your brand is portrayed.

Common reputation risks include:

• Inconsistent messaging across your website, social profiles, and media coverage confusing AI about your positioning.
• Outdated information like old product names, former executives, or discontinued services being cited as current.
• Competitor misinformation or negative reviews dominating the narrative if you’re not actively building positive presence.
• Fragmented brand identity making it difficult for AI to recognise and confidently recommend you.

On the flip side, if your messaging is clear, current, and consistent across channels, AI will reflect that accuracy back to users.

This makes brand consistency more critical than ever. When your messaging, product names, leadership details, and positioning align across PR, SEO, and social, you make it easier for AI to recognise and represent you correctly.

A unified brand builds trust with both people and algorithms.

5. How we measure success is changing

In an AI-driven world, the buyer journey is no longer linear. People move between AI summaries, social posts, reviews, and websites before deciding who to trust. Success isn’t just about clicks or traffic anymore; it’s about being visible, recommended, and ultimately chosen.

Here’s what AI visibility success looks like at different stages of the buyer journey:

• Early research: Being cited as a trusted source and recommended as a leader in AI-generated results.
• Active evaluation: Showing up consistently across channels where your audience is active, building familiarity and trust.
• Decision-making: Attracting fewer but higher-quality visitors who are more informed and ready to convert.

Traditional metrics like organic traffic and click-through rates still matter, but they need to sit alongside new indicators of AI visibility. You may see less overall traffic, but the visitors you do get will be further along in their journey.

What’s more, a sizeable market is emerging for AI visibility tracking tools, each introducing their own proprietary metrics to measure brand presence in AI-generated answers. These tools can help you understand how often you’re being recommended or cited, but they’re only part of the picture.

Lead and revenue growth will remain the ultimate signals of success, even if attribution is becoming messier (it already was, thanks to cookie deprecation and multi-touch journeys).

Despite the messiness, what’s crystal clear is that companies will need to draw new baselines for these metrics and move towards a more integrated measurement framework for digital brand visibility and engagement.

So, what does AI discoverability look like?

AI visibility isn’t a single metric you can track on a dashboard. It’s the cumulative result of how well your brand shows up, how accurately it’s understood, and how confidently it’s recommended across AI-powered tools.

In practice, strong AI search visibility comes down to three key outcomes.

1. Getting recommended

• What it means: When someone asks an AI tool like ChatGPT or Perplexity “What’s the best marketing automation platform for a mid-sized B2B company?” your brand appears in the answer as a credible solution worth considering.
• Why it matters: This is what most brands care about most, because it directly influences buying decisions. Getting recommended means AI tools see you as relevant and trustworthy at the exact moment users are evaluating their options.
• What influences it: Brand recognition, customer reviews, media coverage, industry awards, analyst reports, and how frequently you’re mentioned alongside competitors in trusted sources. AI tools look for patterns of credibility and relevance across multiple channels before confidently recommending a brand.

2. Getting cited

• What it means: AI tools reference your content, research, or expertise when answering broader questions about your industry. You might not be the product being recommended, but your brand is shaping the conversation.
• Why it matters: Being cited builds thought leadership and keeps your brand visible throughout the research phase, not just at the point of purchase. It positions you as an authority and keeps you top of mind as buyers educate themselves.
• What influences it: High-quality, original content that demonstrates expertise, published research or data, bylined articles in industry publications, explainer videos on YouTube, and thought leadership on platforms like LinkedIn. AI tools cite sources that provide unique insights and credible information.

3. Getting represented accurately

• What it means: When AI tools mention your brand, they get the facts right. Your messaging, product details, leadership information, and positioning are clear and consistent.
• Why it matters: AI doesn’t inherently know anything about your brand. It learns from training data, information it retrieves actively from web-based sources, and in some cases via APIs. If that information is inconsistent, outdated, or incomplete, AI will reflect that back to users, damaging your reputation or leaving you out entirely.
• What influences it: Consistent messaging across all channels, up-to-date information on your website, aligned PR and social media communications, accurate listings on review sites and directories, and clear, structured content that AI can easily parse and understand. It’s reputation management for the AI era.

Key takeaways: three strategies to improve AI visibility

Given everything we’ve covered about how AI is reshaping search and brand visibility, what should you actually do?

It comes down to three fundamental strategies:

1. Promote a clear and consistent brand identity

LLMs learn about your brand from every mention across the web. If your messaging, product names, or positioning vary between channels, AI struggles to form a coherent understanding of who you are:

• Start by checking how your brand appears in LLM-generated answers using tools like Peec AI, or run manual checks through ChatGPT, Perplexity, or Google’s AI Mode.
• Look for inconsistent messaging, outdated information, or confusing jargon.
• Create clear brand guidelines and ensure everyone representing your brand publicly works from the same playbook.

2. Build brand trust and recognition in the right spaces

Building trust isn’t about being everywhere; it’s about being visible and credible where it matters most.

Focus on channels where your credibility is recognised: industry publications, analyst reports, review sites, LinkedIn, forums like Reddit, speaking engagements, and relevant awards.

Remember: relevance matters. One mention in a highly respected publication can carry more weight than dozens of low-quality backlinks.

3. Produce high-quality, unique, and user-focused content

Standard SEO principles still apply – Google’s Gary Illyes confirmed you don’t need separate AEO or GEO strategies.

However, the quality benchmark is rising.

With AI tools flooding the internet with generic content, yours needs to:

• Demonstrate genuine expertise
• Answer real questions
• Use conversational language
• Be well-structured so AI can easily parse it.
• Appear in a variety of multimodal formats

Quality always beats quantity.

How to make AI work for you

Here’s the (perhaps slightly controversial) reality: AI visibility is just an outcome of good marketing, combined with a strong understanding of:

• How LLMs work to retrieve, synthesise and present information from across the web
• How your customers search for answers and make decisions
• How authority and trust are built in your industry

Build a clear brand, earn credibility in the right places, create content that actually helps people, and show up consistently. Do that, and AI tools will find you, cite you, and recommend you.

The hard part is doing it all well and keeping it coordinated. That’s where Definition comes in. Our integrated approach to brand, PR, SEO, and content ensures you’re not just ticking boxes, but building genuine visibility and authority that lasts.

Get in touch with our B2B comms experts today.

Written by Matthew Robinson, Senior PR and SEO Strategist at Definition on 21/11/2025

AI visibility FAQs

1. What does AI visibility mean for brands?

AI visibility is about how easily artificial intelligence tools like ChatGPT, Perplexity, or Google’s AI Overviews can find, understand, and accurately represent your brand. The more consistent, credible, and recognisable your online presence, the more likely these systems are to recommend or cite you in their answers.

2. How is AI visibility different from SEO?

Traditional SEO focuses on ranking higher in search engine results pages, while AI visibility focuses on being featured in AI‑generated answers. SEO drives clicks to your website; AI visibility ensures your brand is discovered and represented accurately even when users don’t click through.

3. Why is AI visibility important in 2025 and beyond?

As AI tools increasingly deliver direct, conversational answers, fewer users visit websites through traditional searches. Strong AI visibility ensures your brand still appears in those answers, protecting discoverability, authority, and customer trust as online behaviour evolves.

4. How can I improve my brand’s AI visibility?

You can strengthen AI visibility by keeping your brand information consistent across all channels, earning credible mentions and backlinks from trusted sources, and publishing original, well‑structured content that demonstrates expertise and is easy for AI to interpret.

5. How should I measure AI visibility success?

Success isn’t just about traffic. Metrics now include how often AI tools recommend, cite, or accurately represent your brand. Combined with traditional measures like leads and brand trust, these indicators show how visible your brand truly is in an AI‑driven landscape.