Is Your Brand Visible to LLMs?

For more than two decades, digital discovery followed a familiar formula: optimise for Google, climb the search results, buy ads when necessary. Today, that model is undergoing a significant overhaul.

As consumers increasingly discover products through AI assistants rather than traditional search engines, brands are racing to secure visibility inside LLMs, a fundamental shift from ranking on pages to being named inside answers. The competition has moved away from page rankings to being named within the answer itself.

Consumers are increasingly turning to generative AI tools such as ChatGPT and Gemini to research products, compare services, and make purchase decisions. Traditional search behaviour has changed dramatically. Recent data from LLMrefs suggests that more than 80% of searches now end without a click to an external site, as AI-generated summaries and direct answers satisfy user intent before they ever visit a webpage. 

This brings major implications for how brands think about visibility online.

“LLM search will surpass Google by around mid-2028,” says Siddhesh Tiwatne, Founder and CEO of AI search visibility and content generation platform Erlin.ai, in a conversation with AIM, describing the pace at which engagement with AI search interfaces is growing. According to him, traffic from LLM interfaces converts two to three times better than traditional channels because users complete much of their research inside the AI system before landing on a brand’s website.

The New Battleground for Brand Discovery

Growth forecasts for AI-based search support this sense of momentum. Reports suggest that, if current trends continue, the share of search activity powered by language models could overtake traditional search overall by around 2030. This signals a future where conversational discovery may become the dominant way people explore the internet.

This raises the question of whether AI knows a brand well enough to recommend it. For many companies, the way to influence that outcome is through a new category of optimisation focused on how brands are represented inside AI answers.

Erlin.ai positions itself as a platform that helps brands understand how they appear in large language model outputs, identify representation gaps, improve structured data, and strengthen signals that influence how AI systems interpret brand information. Rather than competing for a top spot on a link list, brands are now competing to be included in the answer itself.

But this shift is not limited to early-stage startups.

Chairman of digital engineering services company Fulcrum Digital, Rajesh Sinha, describes a similar evolution from traditional Search Engine Optimisation (SEO) to what he calls Answer Engine Optimisation (AEO) and Generative Engine Optimisation (GEO). Through its internally developed product RankAbove.ai, Fulcrum is helping larger enterprises adapt to what he frames as “algorithmic enterprise optimisation.” 

“It’s not just SEO anymore,” Sinha says. “It’s about being structurally legible to generative systems.”

RankAbove.ai analyses how brands are represented across digital ecosystems and optimises structured data for AI consumption, strengthening entity-level clarity so that large language models can accurately retrieve and reference them. Initially developed for Fulcrum’s own e-commerce teams, the product is now being positioned as a subscription-based SaaS layer for digital-first brands navigating this new discovery environment.

The industry shift makes intuitive sense when viewed through the lens of how search results are becoming more conversational. In recent years, AI-generated summaries now appear in approximately 13-18% of all search queries globally, nearly doubling as generative features are integrated into mainstream search experiences. 

In queries where these AI summaries are present, traditional click-through rates can drop below 8%—a stark departure from classic SEO expectations. Together, these trends show that visibility inside AI answers is becoming at least as important and in some cases even more so than ranking on a traditional search result page.

While still early, the shift towards AI-led discovery is accelerating. Generative systems now process billions of queries each month, with an increasing share related to commerce, services, and product research, domains that were previously run on traditional search engines. 

Many marketers see a material competitive shift emerging over the next three to five years, particularly as AI agents become more personalised, transaction-aware, and embedded directly into browsers, operating systems, and commerce platforms.

Despite this momentum, there are challenges. Language models remain opaque in how they prioritise sources or determine relevance, and brands have limited control over how they are represented. Over-optimisation of AI systems could risk skewing information, while under-optimisation risks invisibility.

Visibility in a World Without Clicks

Yet, what is increasingly clear is that websites and advertising are unlikely to disappear. A brand’s website remains the only digital real estate it fully controls and serves as a primary source of truth from which AI systems learn and cite information. Advertising models are also evolving rather than vanishing outright, as experiments with sponsored responses and contextual placements begin appearing across major AI platforms.

Still, not everyone believes the balance of power will remain the same. Praveen Sharma, CEO of Housing.com and a former Google marketing head, notes that he sees Google continuing to play the same dominant role in traffic distribution, even if AI-native interfaces become the primary gateway to the internet.

That transition may accelerate further with the rise of agentic browsers. Unlike traditional search engines, agentic systems are designed to complete tasks, including end-to-end travel booking, comparing products, and form filling, often without exposing the user to multiple websites. In such environments, visibility becomes less about attracting a click and more about being selected by an AI system that understands context, preference, and intent.