How AI search is changing the way customers find your business

A quiet shift happened over the past year. People stopped typing keywords into Google and started asking questions the way they’d ask a colleague: “which hotel here has the best view,” or “who’s a reliable insurance broker in this area.” The answer often comes straight from an AI assistant, complete with two or three recommended businesses, before the person ever visits a search engine results page.

This is generative engine optimization, known as GEO, and it works alongside traditional SEO rather than replacing it. Understanding how it works has quickly become one of the more valuable things a business owner can learn about digital marketing right now.

How AI assistants pick their answers

Tools like ChatGPT, Perplexity, and Google’s AI Overviews search the web in real time, pull details from a handful of pages, and combine them into a natural response. Unlike a traditional search engine, which hands the user a list of links to sort through, these tools hand the user a finished answer, often citing just two or three sources.

The pages that get cited tend to share a few traits. They state facts clearly near the top of the page, rather than opening with a long brand story. They include specific, concrete details such as prices, hours, and exact services offered. They get corroborated by other trustworthy sources across the web, from review platforms to industry publications. And they stay current, since outdated information tends to erode the model’s confidence in a source.

Why this matters for local and service-based businesses

This shift matters most for exactly the kind of businesses that once relied heavily on word of mouth and, more recently, on ranking well in Google Maps: restaurants, hotels, salons, clinics, insurance agencies, schools, and boutique retailers. When the modern version of word of mouth happens inside a chat window, a business needs a presence there too.

A hotel page that reads “an unforgettable stay awaits” gives an AI model almost nothing to work with. A page that reads “rooms with private balconies, late checkout available on request, a five-minute walk to the old town” gives the model concrete material to recommend confidently, and gives a real customer a genuine reason to book. The same logic applies whether the business sells insurance policies, hosts weddings, or runs a fitness studio.

Three practical steps for any business

Lead with substance. Open service pages with the exact answer a customer would want: what’s offered, for how much, and for whom. Save the brand story for further down the page, where a human reader who’s already interested can enjoy it.

Keep details consistent everywhere. Business hours, address, and pricing should match across the website, the Google Business Profile, and any directory listing. Consistency across these sources builds the kind of trust these systems tend to reward, while conflicting information creates the kind of doubt that pushes a business out of the running entirely.

Earn mentions beyond the website. A feature in a local publication, a detailed review on an industry platform, or a mention in a well-regarded directory carries real weight, since AI models draw heavily from sources considered independently credible, rather than relying solely on what a business says about itself.

A closer look at structured data

One technical detail worth understanding: AI systems rely heavily on structured data, a behind-the-scenes markup added to a webpage that explicitly labels information such as business hours, pricing, reviews, and service categories. Think of it as a translation layer that removes guesswork for the machine reading the page. A restaurant page with proper schema markup for its menu and hours gives an AI assistant a precise, unambiguous source to pull from, while a page without it forces the model to infer details, and inference introduces the kind of uncertainty that often results in the page being skipped altogether.

Keeping an eye on results

The analytics tools for this space are still developing, so a simple habit helps in the meantime: periodically ask AI assistants the kinds of questions a customer might ask, and note whether your business shows up in the answer. Over time, this builds a clear picture of where the content needs sharper, more specific details, and where it’s already working well.

Watching website analytics for referral traffic from AI platforms offers another useful signal, since a visit arriving from a chat tool usually means the assistant cited the site directly in its answer.

The bigger picture

Search is splitting into several parallel experiences at once: traditional search results, AI-generated conversational answers, and voice assistants, all drawing from much of the same underlying content. A business that keeps investing purely in old-style keyword tactics may see diminishing returns as more people shift toward asking an assistant directly. A business that invests in clear, specific, well-structured content built around real, verifiable details positions itself well for both the search engines of yesterday and the AI assistants shaping how people find businesses today.

The principle underneath all of this hasn’t actually changed. Good marketing has always meant becoming the most useful, most trustworthy answer to the question a real customer is asking. The tools evolved. The goal stayed the same.

If you’d like to read the complete article, you can find it on our Medium profile, under AOM Central, in our article. Article updated September 25.