Something changed in how people find local businesses, and most owners haven't caught up yet.
When someone asks ChatGPT, Perplexity, or Google's AI "best Italian restaurant near me," they don't get a list of 10 links to sort through. They get a direct answer, often with specific details about why that place is recommended.
Where does that answer come from? Your reviews.
AI is reading your Google reviews, summarizing them, and using that information to recommend (or not recommend) your business. This is happening right now, and it's only going to accelerate.
How AI Answers Local Business Questions
When someone asks an AI assistant for a local recommendation, here's roughly what happens:
The AI pulls information from multiple sources: Google Business profiles, reviews, websites, local directories, and sometimes social media. It then synthesizes all of that into a direct answer.
For local businesses, reviews are one of the richest data sources available. They contain specific details about real customer experiences, updated recently, with enough volume to identify patterns.
So when someone asks "best coffee shop for working in [city]," the AI doesn't just look for high-rated coffee shops. It looks for reviews that specifically mention things like "quiet atmosphere," "good wifi," "plenty of outlets," or "lots of seating."
The businesses that get recommended are the ones whose reviews contain the right details.
Generic Reviews vs. Specific Reviews
This is where it gets interesting for business owners.
A review that says "Great food, nice service!" doesn't give AI much to work with. It's positive, but it's not useful for matching specific queries.
A review that says "Best carbonara I've had outside of Rome. They make their own pasta daily, and the outdoor patio is perfect for date nights" gives AI a lot to work with:
- Italian food (specifically carbonara)
- High quality ("best outside of Rome")
- Fresh ingredients ("make their own pasta daily")
- Good atmosphere ("outdoor patio")
- Date-appropriate ("perfect for date nights")
That second review can match queries like "romantic Italian restaurant," "best pasta in [city]," "restaurants with outdoor seating," and "where to go for authentic Italian."
The first review matches almost nothing specific.
What This Means for Your Business
If AI is increasingly how people find local businesses, then the content of your reviews matters more than ever.
It's not enough to have good reviews. You need reviews that contain specific, relevant details about what makes your business good.
Think about what you want to be known for, and whether your reviews actually say those things.
A mechanic who wants to be known for fair pricing needs reviews that mention "fair price," "honest quote," or "didn't try to upsell me."
A restaurant that wants to be known for brunch needs reviews that mention "amazing brunch," "best mimosas," or "weekend breakfast spot."
A salon that wants to be known for color work needs reviews that mention "balayage," "highlights," "color correction," or specific techniques.
Your reviews are training data. Make sure they're training AI to recommend you for the right things.
How to Get More Specific Reviews
You can't control exactly what customers write, but you can influence it:
Ask at the right moment. The more recently they experienced something specific, the more likely they are to mention it. Ask right after a service when the details are fresh.
Give them a hook. Instead of "Would you leave us a review?" try "If you enjoyed the [specific service], we'd love if you mentioned it in a Google review." This primes them to include specifics.
Respond to reviews with specifics. When you respond to reviews, you can add context: "So glad you enjoyed our housemade pasta! We make it fresh every morning." This adds searchable details to the review thread.
Encourage detail organically. Train your staff to have conversations that highlight your differentiators. If customers are thinking about what makes you special, they're more likely to write about it.
The Shift From "10 Blue Links" to "One Answer"
Traditional SEO was about ranking in a list of 10 results. Users would scan the list and click the one that seemed best.
AI search is different. Instead of showing options, it gives one answer (or a very short list). The goal isn't to be in the top 10, it's to be the one that gets recommended.
This raises the stakes significantly. In traditional search, being #3 still got you clicks. In AI search, being #3 might mean you don't get mentioned at all.
The businesses that will win in this environment are the ones with:
- High volume of reviews (more data for AI to work with)
- Specific details in reviews (more ways to match queries)
- Recent reviews (signals the business is still good)
- Consistent quality signals (high rating across many reviews)
Generic reviews and thin review profiles will increasingly get overlooked.
AEO: Answer Engine Optimization
There's a term emerging for this: AEO, or Answer Engine Optimization. It's the practice of optimizing your online presence not just for search rankings, but for AI recommendations.
For local businesses, AEO mostly comes down to reviews. Your Google Business profile matters. Your website matters. But reviews are the richest, most dynamic source of information that AI uses to understand and recommend your business.
The businesses thinking about this now will have an advantage over those who figure it out later.
The Bottom Line
AI is already reading your Google reviews and using them to answer questions like "best [business type] near me." This is happening now, and it's going to become more important as more people use AI assistants for local recommendations.
Your reviews aren't just social proof anymore. They're training data for the systems that will increasingly determine whether you get recommended.
The businesses that collect lots of reviews with specific, relevant details will get recommended. The ones with thin profiles or generic reviews will get overlooked.
Think about what you want to be known for, and make sure your reviews actually say it.
Frequently Asked Questions
Does ChatGPT use Google reviews for recommendations?
Yes, AI assistants like ChatGPT pull from multiple sources including Google reviews when answering questions about local businesses. Reviews provide specific, recent information about real customer experiences that AI uses to make recommendations. The details in your reviews influence whether and how AI recommends your business.
What is AEO (Answer Engine Optimization)?
AEO stands for Answer Engine Optimization. It's the practice of optimizing your online presence for AI assistants and answer engines, not just traditional search rankings. For local businesses, AEO largely comes down to having lots of detailed, recent Google reviews that give AI specific information to work with when recommending businesses.
How do I get more detailed Google reviews?
Ask for reviews right after service when details are fresh. Give customers a specific hook like "If you enjoyed the [specific service], we'd love if you mentioned it." Respond to reviews with additional context. Train staff to highlight your differentiators in conversations so customers are thinking about specifics when they write. You can't control what customers write, but you can influence it.
Why do specific reviews matter more than generic ones?
AI uses review content to match businesses with specific queries. A review saying "Great food!" doesn't help AI answer "best place for authentic tacos" or "restaurant with outdoor seating." A review mentioning "incredible al pastor tacos" and "beautiful patio" matches both. Specific reviews help you get recommended for more types of searches.
How will AI change local search?
AI is shifting local search from "10 blue links" to "one answer." Instead of showing users a list of options, AI gives direct recommendations. This raises the stakes—being #3 in traditional search still got you clicks, but AI might not mention you at all. Businesses with detailed reviews and strong profiles will get recommended; those without will increasingly get overlooked.