It was easy but primitive in the early internet days to discover a local business: you’d enter a few keywords into a search engine or flip through an online directory, and you’d be given a list of sites. With time, search engines like Google started improving the process by adding “near me” features, maps, and reviews, which made it easier for people to find nearby stores, restaurants, and services. Geographic Search Engine Optimisation, or Geo SEO, is the process of making businesses show up in local search results because of this advancement. Large Language Models (LLMs), the software behind applications like ChatGPT and Gemini, just launched in the market. They are more advanced than simply listing sites.

Now comes a new player: Large Language Models (LLMs), the artificial intelligence minds powering such products as ChatGPT and Gemini. LLMs don’t just itemize websites. They understand queries, read between the lines, and deliver responses in natural language. And when those responses have a spatial dimension, eg the nearest coffeehouse, the closest car repair shop, or the cheapest hotel, LLMs start to redefine the entire field of Geo SEO.

Classic SEO has been keyword-centric. When someone typed “pizza Athens delivery” into Google, the businesses with the perfect mix of keywords, backlinks, and page speed would appear. Geo SEO added another layer on top: maps, opening hours, and reviews narrowed down the search to close and relevant options.

But LLMs require a different mode of interaction. Instead of keywords, people now ask questions as they would question someone they know. This is no longer a matter of keyword matching. It is now about understanding intent, sifting through options, and recommending the best match. For businesses, this shift runs deep. It’s about being discovered not among ten results on a search list, but as that single, AI-recommended answer.

Small businesses typically get outshined by monolithic brands in traditional SEO where ad campaigns and backlink efforts cost an arm and a leg. LLM-based search rebalances the equation. Such models rely significantly on organized information, reviews, and plain web signals rather than expensive marketing pushes.

A small-town coffee shop will never out-Starbucks at old-fashioned SEO, but with right business listings, steady hours, a digital menu, and rave reviews that contain the terms “vegan” or “late-night,” an LLM can easily recommend it as the best choice for someone in the area.

Preparation for this new world involves some hands-on steps: profile updation on Google Business and Yelp, urging customers to leave long reviews, and having information consistent on sites and directories. Even creating content that answers question-like questions (“Where can I find gluten-free pastries in Heraklion?”) helps AI tools recognize the business as relevant for real-world queries.

Basic Steps to Prepare for AI Geo SEO

Target	Action	Benefits
Appear on Google AI	Update your Google Business profile (hours, categories, photos)	Increases the chance of being recommended by AI Overviews
User trust	Ask for authentic and detailed reviews from customers	LLMs draw content from comments for recommendations
Information consistency	Keep the same information on site, social media and directories	Enhances reliability in AI results
Content of intentions	Create articles like “where can I find…” or “what is the best…”	AI assistants better recognize local relevance

The way people make decisions is also changing with technology. In the past, a search began with typing, followed by clicking through a series of sites, reading descriptions or menus, and finally calling or visiting. Today, many consumers bypass sites altogether: they read reviews on Google Maps, compare ratings, and head straight to a business.

With LLMs, this is even shorter. A customer can ask their phone or AI assistant a question and receive a direct recommendation — and usually even the option to book, order, or reserve immediately. The user no longer searches; they simply ask, and the AI answers.

This shift reduces friction, which is good for consumers, but raises the stakes for businesses. If your business is not known to the AI to be relevant, you may not be in the conversation at all.

Geo SEO’s past is a three-part narrative. Once upon a time, local search was all about directories and keywords. Now, it’s all about mobile-friendly sites, maps, and reviews. And in the near future, it will be all about LLM-powered assistants that integrate personal tastes, real-time location, and conversational intent into one suggestion.

Try saying to your AI assistant, “Find me a nearby gym with free day passes that’s not crowded today.” This request combines location, business offerings, and even real-time information like crowd levels. Search engines are moving towards just this level of personalization, and early adopters in small businesses will reap a tremendous advantage.