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Restaurant Discovery

AI search and restaurant discovery: what actually changes

Guests increasingly ask AI assistants where to eat instead of scrolling results. The inputs those assistants rely on are the same ones local search always used — which means the work that builds visibility has not changed, but the cost of getting it wrong has gone up.

Alex Opsenica, founder of Moolah Media

Alex Opsenica · Founder, Moolah Media

4 min read
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A growing share of guests no longer type "italian restaurant dublin 2" and scan a page of results. They ask an assistant — ChatGPT, Gemini, Google's AI Overviews — "where should I take my parents for dinner near Grafton Street, somewhere quiet, good fish, booking for Saturday." The answer comes back as a shortlist of three or four names, often with no obvious way to be result five.

That shift is real, and it is worth taking seriously without taking the hype seriously. This piece separates what has genuinely changed from what has not, and what a restaurant should actually do about it.

How AI assistants decide which restaurants to name

When an assistant recommends restaurants, it is not visiting them. It is reading the web's accumulated record: Business Profiles, reviews across platforms, menus, press coverage, guides, directories and websites. The recommendation is a compression of everything written about the venue — which means the recommendation is only as good as the record.

Google has been explicit that its AI features in Search draw on the same eligibility and quality systems as its other results: there is no separate optimisation for being cited, and no markup that buys inclusion. Content that is accurate, specific and well-described is what surfaces.

Source: Google Search Central — AI features and your website — Google's own documentation on how AI Overviews and AI Mode use website content, and what controls exist.

What has genuinely changed

  1. Queries are longer and more specific. "Quiet restaurant for a business dinner, good wine list, near Stephens Green" replaces "restaurant dublin 2". Venues whose public record answers those specifics get named; venues with a generic record do not.
  2. The shortlist is shorter. A map pack shows three and a results page shows ten; an assistant often names three or four and stops. The gap between being named and not being named widens.
  3. Consistency matters more, not less. If your hours, cuisine and price band disagree across platforms, the assistant inherits the confusion — and a confused source is quietly dropped.
  4. Review text is read, not just counted. Assistants summarising "what people say" draw on review language: the service, the noise level, the dishes guests mention. Generic review profiles produce generic summaries.

What has not changed

Every input an assistant can use is an input you already control or influence: an accurate Business Profile, a steady flow of genuine reviews, a website with readable menus and real detail, consistent listings, and coverage in publications people trust. There is no new discipline called "AI optimisation" that replaces this. There is only the old discipline, with a new place its results show up.

The specific details assistants look for

Long conversational queries are answered from specifics. The venues that get named for "somewhere quiet for a business dinner" are the ones whose public record contains the word "quiet" — in reviews, in their own description, in coverage. This argues for completeness over slogans.

A hypothetical illustration

What to do about it — and what not to bother with

The practical response is unglamorous: complete the record, keep it consistent, and let real service generate the reviews that describe you. Check occasionally what the assistants actually say about your restaurant — ask one the questions your guests ask — and treat any wrong answer as a symptom of a gap in your public record, not a problem with the assistant.

  • Do: ask ChatGPT or Gemini for restaurants like yours in your area, and note who is named and why
  • Do: read the summary the assistant gives of your own venue — it is a free audit of your public record
  • Do not: chase speculative markup or "AI submission" services — there is no such pipeline
  • Do not: publish thin content aimed at assistants; it weakens the record rather than strengthening it

The venues that win this shift are the ones that were already describable: specific about what they are, consistent about the basics, and reviewed by real guests in real words. That was the work before AI search, and it is the work after it.

Common questions

Can I pay to appear in ChatGPT or AI Overview recommendations?

No. There is currently no paid inclusion in AI assistant recommendations. They are assembled from the public record — profiles, reviews, websites, coverage — which is why accuracy and completeness are the only levers.

Is there special markup or code that gets a restaurant into AI answers?

No dedicated markup exists. Standard structured data for your hours, menu and location helps machines read your site correctly, and Google's documentation confirms AI features draw on the same quality systems as the rest of Search — but there is no tag that buys a citation.

Will AI search replace Google Maps for finding restaurants?

It is more likely to sit alongside it. Spontaneous proximity searches — "restaurants near me" while standing on a street — still resolve in Maps. Considered, specific requests increasingly go to assistants. A complete public record serves both.

How do I check what AI says about my restaurant?

Ask the assistants directly, the way a guest would: your name, your cuisine, your area, and the occasions you want to be chosen for. Wrong or missing answers point at gaps in your public record, and those gaps are fixable.

Working on this yourself? How Moolah builds that record.

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Written by

Alex Opsenica, founder of Moolah Media

Alex Opsenica

Founder, Moolah Media

Founder of Moolah Media, a specialist restaurant growth and local SEO agency based in Ireland, working directly with hospitality operators on search, Google Business Profile and bookings.

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