How to Get Your Business Recommended by ChatGPT and Google AI in 2026

A homeowner who needs a mover used to open Google, scan the map pack, and click two or three websites.

A growing number now type "who's the best moving company in Berkeley" into an AI assistant and read a short list of three names with a sentence of reasoning each. They do not see ten blue links. They see a recommendation.

If your business is not one of the three, you were not outranked. You were not considered.

That is a different failure mode than losing a search ranking, and it needs a different fix.

We can see this shift in our own Search Console data. Over a recent 90-day window, roxfire.io picked up impressions for queries including "check brand visibility in chatgpt", "ai content visibility in chatgpt search", and - the one that says the most - "ai visibility agency for water damage restoration".

That last query is a restoration contractor who has worked out that AI assistants are sending work somewhere, and it is not to them, and they are looking for help.

That search did not meaningfully exist two years ago. Business owners are ahead of most agencies on this.

Generative Engine Optimization, or GEO, describes work aimed at improving how a business appears in AI-generated answers.

It is not a replacement for SEO. The foundations overlap heavily: a site that is crawlable, accurate, specific, and well-regarded by third parties performs better in both. But the mechanisms differ enough that a business can be strong in one and invisible in the other.

Traditional SEO aims to rank your page; GEO aims to get your business named in an answer. SEO optimises your own site; GEO depends heavily on what other sites say about you. SEO targets keyword queries; GEO targets conversational questions. SEO is measured by position and traffic; GEO by mentions, citations, and referrals. SEO rankings are relatively stable and trackable; AI answers vary by phrasing and session.

No technique guarantees an AI recommendation. Anyone selling one is overselling.

Here is the part most advice gets backwards.

When an AI assistant answers "best garage door repair in Tampa", it is generally not browsing your website and forming an opinion. It runs a search, retrieves a handful of pages, synthesises an answer from what those pages say, and cites them.

The pages it retrieves are rarely company websites. They are listicles and roundups - "10 Best Garage Door Companies in Tampa". Directory and review platforms. Local news, chamber, and trade association pages. Forums and community threads where someone asked the same question. Comparison and aggregator sites.

Your own site's claim to be the most trusted garage door company in Tampa carries almost no weight, because every competitor makes the identical claim and models have learned to discount it. What carries weight is a third party saying it.

This produces the central asymmetry: traditional SEO is about making your page rank. AI visibility is about appearing on the pages the assistant reads.

A contractor ranking third in the map pack can be entirely absent from every roundup article in their city, and the assistant will never name them.

1. Presence in third-party roundups. The biggest lever and the most neglected. If five "best movers in [city]" articles exist for your market and you appear in none, you have no path into an AI recommendation for that query. Getting included is outreach work, closer to link building than to publishing: find who publishes those lists locally and give them a reason to add you.

2. Specific, repeatable facts. Assistants reproduce concrete details - years in business, service area, licence numbers, specialisations. Vague positioning gives a model nothing to quote. "Quality service you can trust" is noise. "Family-owned since 1998, serving Alameda and Contra Costa counties, specialising in piano and antique moves" is repeatable.

3. Review volume and recency across multiple platforms. Assistants pull sentiment from more than one source. A business with 400 Google reviews and nothing anywhere else reads as thinner than one with 150 spread across Google, Yelp, and an industry platform.

4. Consistent business information everywhere it appears. Standard local SEO hygiene, but it matters more here. Conflicting name, address, or phone data makes a business harder to resolve as a single entity, and an assistant that cannot confidently resolve you will name a competitor it can.

5. Structured data that matches visible content. Organization, LocalBusiness, Service, and FAQPage schema help systems parse what a page says, which is part of on-page SEO. Schema does not guarantee citation, and markup that contradicts the visible page is worse than none. Specificity matters more than markup, but both help.

You do not need a tool or an agency to find out where you stand. You need about an hour.

Step 1 - Build your prompt set. Write 10 to 15 prompts the way a customer would actually phrase them. Questions, not keywords. "Who's the best [trade] in [your city]?" "I need emergency [service] in [city], who should I call?" "Recommend a reliable [trade] near [neighbourhood]." "Who are the top-rated [trade] companies in [city]?" "I'm moving to [city], which [trade] do locals use?"

Step 2 - Run each across every assistant your customers use. Use a fresh session with no chat history or personalisation, because your own history will skew results toward businesses you have already discussed.

Step 3 - Record three things per prompt. Were you named at all? What position? And critically, which sources were cited?

Step 4 - Read the citations. This is the step people skip, and it is where the entire answer lives. The cited pages are the ones you need to appear on. If the same three local roundup articles get cited across most of your prompts, you now have a precise, finite target list. That is your outreach plan, and it is usually shorter than you expect.

Step 5 - Repeat quarterly. These systems change often enough that a one-time snapshot goes stale.

Named consistently: document which sources are driving it and protect those relationships. Verify the details being reported about you are accurate - assistants will repeat an outdated service area or a wrong phone number with complete confidence.

Named occasionally: you are usually close. Compare the prompts that fail against those that succeed. The gap is normally a specific service or neighbourhood you are not associated with anywhere on the open web.

Never named: your work is not on your website. It is getting onto the pages assistants already read. Start with the citation list from step 4, work through it in order, re-test in 90 days.

Appearing in an AI answer is not the objective. Customers are.

Track whether visibility work moves relevant website visits, qualified inquiries, phone calls, and booked jobs. Attribution from AI platforms is incomplete and will stay that way for a while, so combine what analytics shows with realistic interpretation rather than demanding perfect measurement.

A contractor who gets named in three cities and sees no change in call volume has learned something useful: the prompts they tested are not the prompts their customers use.

Nobody has a reliable, repeatable method for guaranteeing an AI recommendation. These systems are not stable, retrieval behaviour changes, and the same prompt can return different answers on different days.

What is stable is the underlying logic: assistants summarise what the web says about you. Businesses described well, specifically, and in multiple credible places get recommended. Businesses that exist only on their own website do not.

That was broadly true before AI search. It is now considerably less forgiving.

How does ChatGPT decide which local businesses to recommend?

In most cases it searches, retrieves a handful of pages, and synthesises an answer from them. Those pages are usually third-party sources - roundups, directories, review platforms - rather than company websites. Being described well on those pages matters more than what your own site claims.

Can a business pay to be recommended by ChatGPT?

Sponsored placements and organic recommendations are separate experiences. Buying advertising should not be assumed to influence organic AI recommendations, and any vendor claiming it does is worth questioning closely.

Is GEO different from SEO?

They overlap heavily but are not identical. SEO aims to rank your page; GEO aims to get your business named in a generated answer, which depends far more on third-party coverage. Strong SEO fundamentals remain a prerequisite rather than something GEO replaces.

Does schema markup guarantee AI citations?

No. Structured data helps systems parse a page accurately, which is useful, but it guarantees nothing. Markup that contradicts the visible content is actively harmful.

How do I check whether AI assistants recommend my business?

Write 10 to 15 customer-phrased questions, run them in fresh sessions across the assistants your customers use, and record whether you are named and which sources are cited. Repeat quarterly. The cited sources are the actionable output - they tell you exactly which pages you need to be on.

How long does AI search visibility take to improve?

There is no reliable timeline. Where the gap is third-party presence, improvement follows whenever those pages update, which can be weeks or months. Where the gap is reputation or review depth, it is slower.

Does my Google Business Profile affect AI recommendations?

An accurate profile supports local discovery within Google's own products, and review data from it is widely referenced. Its influence on any specific AI answer depends on the assistant and the question, so treat it as necessary rather than sufficient.