Ask ChatGPT about plumbers in your city and the response may name businesses, cite sources, show local information, or decline to recommend one. The result varies by product, prompt, market, and date.
BrightLocal's 2026 Local Consumer Review Survey reported that 45% of respondents had used tools such as ChatGPT, Gemini, or Perplexity for local business recommendations in the past year.
BrightLocal also published a 6% figure in 2025, but the survey questions and context were not the same. Treat 45% as a 2026 snapshot, not proof that one identical measure rose from 6% to 45% in twelve months.
If you want to know whether that behavior already affects your market, run the Cheers AI Visibility Grader before guessing. It is the fastest way to compare your business, competitors, and source trail across AI answers.
How consumers use AI to find local businesses
The age group with the highest reported use was 30 to 44, at 64%. That group includes many home-services buyers, but the survey does not show that every respondent replaced Google or received a single-business answer. The operating implications are covered in How Home Services Brands Get Recommended by AI.
First Page Sage publishes a live standalone-chatbot market-share tracker that currently ranks ChatGPT first. The page changes as new monthly estimates are published, so this article does not preserve an unsupported historical percentage without an archived source.
ChatGPT hit 800 million weekly active users by October 2025, up from around 400 million in early 2025.
Google also announced at I/O 2026 that AI Mode passed 1 billion monthly users and that AI Overviews can now move directly into AI Mode conversations. BrightLocal separately reported lower Google review usage in its survey. Those measures show that discovery behavior is broadening, but they do not establish how much traffic moved from one channel to another. For the broader channel analysis, read How AI Is Changing Local Search.
What public sources can establish
OpenAI confirms that ChatGPT search can use third-party search providers, including Bing, and can cite web sources. It does not publish a fixed local-business sequence involving Google reviews, Foursquare, Yelp, BBB, directories, or the business website.
Separate local tests have observed some of those sources in particular answers. Treat the observations as examples to verify in your own market, not as ChatGPT's permanent retrieval architecture.
LocalFalcon analyzed 189,905 ChatGPT search results and compared them to over 16 million Google results. The finding: 83% of restaurants were not visible on ChatGPT, versus just 14% absent from Google results.
Google reviews remain useful customer evidence and part of Google's local ecosystem. Whether another AI product retrieves or cites that evidence is a separate measurement question.
What to inspect around AI recommendations
Each product can retrieve a different source mix, and no public source exposes a universal local recommendation formula. For the source-by-source breakdown, read What Sources Do ChatGPT, Gemini, and Perplexity Use for Local Businesses?.
Review presence on relevant platforms. Review pages can appear in cited results and give customers first-hand context. Maintain legitimate profiles where customers in the category actually look, but do not assume that spreading reviews across four platforms will outperform a stronger profile on one.
Business-information accuracy. Compare the website, profiles, and directories for wrong phone numbers, old addresses, conflicting hours, or different service claims. Harmless formatting differences are less urgent than facts that could send a customer to the wrong place.
Structured data. Applicable JSON-LD can describe visible business facts in a machine-readable format. Google says structured data is not required for AI features, and no public source makes it a universal recommendation factor.
Useful owned pages. Service and location pages should answer real buyer questions and expose accurate business facts. A small website is not automatically ineligible, and publishing more pages does not guarantee a recommendation.
Third-party context. Yext's research found that 86% of citations in its sample came from brand-managed sources, a category that included third-party profiles brands can maintain. Independent sources such as local reporting, trade associations, and customer discussions may also appear. Track the sources in the actual answer instead of treating mentions as a universal trust signal.
The trust factor
BrightLocal's data shows something that might surprise you: 63% of active AI users already trust AI recommendations for local businesses. And 42% of all consumers trust AI recommendations as much as traditional online reviews.
But they're not blindly trusting. 88% of AI users fact-check the recommendations, either by verifying the source (37%) or checking if the review is legitimate (51%). 97% double-check AI recommendations against real reviews at least sometimes.
For many respondents, AI was one step in a broader decision process rather than the final word. A recommendation may lead to a source check, a review check, a website visit, or another search.
Measure both layers where they apply: whether the business appeared in the tested answer and whether the customer-facing sources were accurate and useful when respondents said they fact-checked.
What to do about it
Follow each review platform's policy. Google allows neutral review requests under its rules; Yelp prohibits businesses from asking customers for reviews. Maintain accurate profiles where customers use them, earn feedback according to each platform's policy, and do not create a multi-platform review footprint for an assumed AI benefit.
Audit public business facts. Search for the business across Bing, Foursquare, Yelp, BBB, and relevant directories. Fix wrong addresses, disconnected phone numbers, conflicting hours, inaccurate services, and old destination URLs. Harmless punctuation and address abbreviations are lower priority.
Use structured data where appropriate. LocalBusiness markup can describe services, service areas, hours, contact information, and verified profiles when those facts are visible on the page. Google does not require structured data for AI features.
Check the answers directly. Test the providers, prompts, and markets that matter. Save the answer, cited sources, competitors, and date so the team can distinguish an actual source problem from a one-off response.
Publish pages that earn their URL. A service or location page should answer a distinct buyer question with accurate local detail. Do not create one page per keyword variation or claim that more pages guarantee an AI recommendation.
Establish a baseline now
The useful reason to check now is measurement. A dated baseline lets the team compare future answers, cited sources, and competitors after it fixes a page, profile, directory record, or review workflow.
Do not turn the separate 6% and 45% survey findings into a single adoption curve. Do use the current evidence to justify monitoring the channel alongside Search, Maps, reviews, and booked demand.
Check where your business appears today with the free Cheers AI Visibility Score.
Sources
- BrightLocal: Local Consumer Review Survey 2026
- BrightLocal: AI Trust in Local Search
- First Page Sage: Top Generative AI Chatbots (May 2026)
- LocalFalcon: The AI Visibility Crisis
- Search Engine Land: SOCi 2026 Local Visibility Index Coverage
- TechCrunch: ChatGPT at 800M Weekly Active Users
- Google: A New Era for AI Search (I/O 2026)
- Hook Agency: Brand Authority and AI Search
Dylan Allen-Arnegård is the CEO of Cheers, the local search platform for service businesses.