For years, local marketing had one obsession: the Google 3-Pack. Those three local business listings that appear at the top of Google search results, complete with map and reviews. If you were in the 3-Pack for your key terms, you won. If you weren't, you were fighting for scraps.
That surface is not dead. AI-mediated search adds new ways for people to discover and compare local businesses, so operators now need to measure both.
What the 3-Pack got right
Google's local pack was a brilliant interface for its time. You search "plumber near me," you get three options with ratings, reviews, and a map. It surfaced the most relevant businesses quickly, and it created clear winners: those three spots at the top.
Businesses responded by optimizing for local SEO. Google Business Profile became critical. Review collection became critical. Proximity, relevance, and prominence were the signals that mattered. If your team is still asking whether that work is worth doing, start with Does SEO Still Work in the Age of AI Search?.
This worked because users were willing to choose from a list. They'd click through the top three options, compare reviews, maybe check websites. The 3-Pack gave them options; they made the decision.
For Google's current AI Search guidance, read How Local Businesses Can Show Up in Google AI Search. For the operating checklist behind AI recommendations, see How to Get AI to Recommend My Business.
What AI changes
AI assistants often present a shorter answer than a conventional local results page, but the format varies.
Pro Tip
Test the actual buying prompts in each market. Record whether the answer names one business, several businesses, or only provides general guidance.
The answer may narrow the visible shortlist, but customers can still inspect citations, read reviews, visit websites, or continue searching.
Important
In the 3-Pack, being second or third still got you visibility. In AI recommendations, being just outside the short list often means not being mentioned at all. The shortlist dynamic is much more severe.
The signals are different
Google's local algorithm famously weights proximity heavily. A business closer to the searcher's location gets a boost. This created hyper-local dynamics where a plumber in north Austin might dominate that area but be absent in south Austin.
AI products do not publish one local proximity or reputation formula. An answer to "best plumber in Austin" may use web retrieval, local data, cited pages, or other product-specific systems.
Pro Tip
Do not assume a large review count can overcome a weak service-area fit. Verify which branch the answer names and whether that branch can actually serve the customer.
But it also raises the bar. You can't just be good in your immediate area. You need a reputation that stands out across your entire market.
The transition is happening now
AI adoption for local search is growing fast. Every Google search that triggers an AI Overview, every AI Mode conversation, every ChatGPT user asking for recommendations, and every Perplexity answer with cited sources shifts discovery toward AI-mediated results.
The exact numbers vary by platform, survey, and category. BrightLocal reported 45% use in one 2026 survey, while its 2025 figure came from a different measure and should not be treated as a clean year-over-year trend. Google also reported that AI Mode passed 1 billion monthly users. Traditional search is not dying, and AI is now part of the search behavior local businesses need to observe.
Pro Tip
Establish a dated baseline now so future source, page, and profile changes can be evaluated against the same prompts.
What this means for your strategy
Don't abandon Google Business Profile. The 3-Pack still matters, and GBP optimization helps with both traditional and AI search. But shift your emphasis.
Accurate local proof alongside proximity. You cannot change where a branch is located, but you can accurately publish its service area, hours, services, reviews, and booking path. Review velocity is an operating metric, not a published AI ranking factor.
Relevant public sources. Maintain profiles on the review and directory platforms customers in the category actually use. Record which ones appear in the answers you test.
Business-information accuracy. Keep material facts aligned across the website and profiles. Use applicable schema that matches visible content. Treat llms.txt as an optional proposal, not a ranking requirement.
Monitor AI results directly. Test what ChatGPT, Gemini, Perplexity, and Google AI surfaces show for priority markets. Track appearance, cited sources, competitors, and answer changes alongside Search performance.
Important
Keep investing in the 3-Pack and ordinary Search fundamentals. Add AI visibility measurement rather than replacing proven local search work with an invented ranking playbook.
Further Reading
- ChatGPT Statistics for Local SEO. Key data on AI search adoption and local business impact
- Google Search Central: AI features and your website. Official guidance on AI features, eligibility, crawlability, snippets, structured data, and Search fundamentals
- BrightLocal: Local Consumer Review Survey 2026. Consumer adoption data for AI recommendations and reviews
- Google: A New Era for AI Search (I/O 2026). Official update on AI Mode adoption and Search integration
- Top Generative AI Chatbots by Market Share. First Page Sage's competitive analysis
Dylan Allen-Arnegård is the CEO of Cheers, the local search platform for service businesses.