AI search has rewritten the buying journey and brands are behind

Making a purchasing decision used to be a fairly drawn-out process. Open Google, scan various links, click through multiple sites, compare different options, check reviews, and perhaps ask colleagues and friends. It wasn’t necessarily a smooth process, but rather a fragmented and often time-consuming one. Well, this model is now being dismantled and really rather quickly. 

Today, more and more buying journeys start and end inside an AI interface. Whether it’s ChatGPT, Gemini, Claude, or another large language model (LLM), consumers are no longer sifting through ten different links. Instead, they receive personalised answers following a prompt.

The upshot of this is that the time between the question being posed and a buyer armed with the info to make a decision has practically evaporated. This is a seismic shift in what it means for a brand to be truly visible online.

From search engine to answer engine

Search engines have historically acted as directories. Yes, they present options, but really, users have to do a lot of the legwork themselves. AI search, by contrast, effectively acts as an interpreter. It ingests vast amounts of information and returns a distilled answer tailored to the user’s personal preferences. For example, instead of typing “best running shoes” into Google, users are now able to ask AI – “What’s the best cushioned running shoe for someone training for a half marathon with knee pain?”. 

This shift is massive as the AI effectively becomes the first and possibly the only filter in the buying journey. If your brand isn’t part of the summarised answer that the LLM delivers, it’s as if you don’t exist.

Curiosity has increased but friction has decreased

To be clear, traditional search certainly hasn’t disappeared. In fact, usage has continued to grow steadily. What has changed however is how people use and interact with it.

Consumers no longer make snap decisions after glancing at a few links for comparison. They are now asking more layered, nuanced questions. AI tools are facilitating deeper investigation without any extra effort, meaning buyers are becoming more curious as a result. Any friction in decision-making has been drastically reduced and gone are the days when multiple tabs, inconsistent information, and conflicting reviews meant a buying decision was excessively drawn out. AI has made the experience feel more authoritative and personalised.

It’s the personalisation that really is key here. Not only does AI search answer questions, but it also answers them specifically in context. It factors in historical preferences and defined constraints. Over time, these systems will increasingly anticipate needs as opposed to simply responding to them. The transition from reactive search to proactive recommendation is clear.

Why most brands are invisible

The uncomfortable reality is that many companies are simply not structured to appear in AI-driven answers. For years, SEO strategies were designed around ranking for broad keywords. But now, AI search favours specifics. It prioritises those who clearly articulate and explain the problem they’re solving and the target audiences they serve.

Generalist positioning is losing ground to specialist clarity, and this has presented smaller companies with an opportunity. Large businesses describing themselves in ambiguous language are essentially being downgraded by AI that rewards precise wording.

The brands successful in AI search follow a few key principles rigidly. First, they clearly define both who they are for and who they are not for. Second, they structure their content in ways that LLMs can easily process. Third, they maintain consistent messaging across owned and earned channels. And fourth, they build authority through credible third-party mentions.

AI systems don’t just quickly scan a website. They focus on pinpointing trust signals in your online presence. If you are not referenced in credible publications or industry conversations, this drastically reduces your chances of being included in LLM-generated recommendations.

Share of voice becomes share of recommendation

Whereas traditional search has historically been about ranking, AI search is all about inclusion. Instead of tracking keyword positions, the brands that are truly thinking ahead are tracking “AI visibility” – i.e. how often they are mentioned in relevant AI-generated conversations.

Early case studies are striking. Companies that were previously invisible in AI search environments have seen referral growth surge after optimising their positioning and authority signals. In some cases, the impact of this process has meant AI-driven referrals have increased by multiples, directly impacting revenue growth.

In a way, the mechanism is arguably quite simple. When AI systems recommend you, high-intent traffic follows. In turn, because this recommendation often appears framed as a direct answer, rather than a paid advertisement, the trust dynamic is different. It makes the interface feel neutral, objective, and impartial. That perception alone can accelerate conversion.

What happens next?

We are still in the very early stages of this shift. Phase one is what we’re experiencing now – i.e. consumers using AI tools to research and refine purchasing decisions faster. Phase two is automation. As AI systems accumulate more contextual knowledge about individual users, they will transition from merely answering questions to proactively initiating suggestions. From here, transactions will increasingly happen inside AI interfaces themselves.

AI search has not only shortened the buying journey, but it has also redefined it. Page one of Google is no longer the one and only battleground. Brands that accept the importance of this shift, adapt their positioning, content, and build credibility, will find themselves recommended. Those that don’t may still exist online, but they just won’t be seen.