The news: AI tools are growing in popularity for local search, but trust questions and inaccurate information are getting in the way.

Fifty-two percent of US consumers have used AI in the past 30 days to find or research a local business, per SOCi, up from 9% in 2025. That rises to 63% among millennials—the power users of local AI searches.

However, for 81% of consumers, an AI recommendation kicks off a verification cycle—not direct brand engagement. That’s driving them to check reviews on a site like Google, look at a business’s owned social media, contact the business directly, or search the name.

What’s leading to this need for vetting?

• Trust in AI hasn't increased for 73% of consumers in the past year.
• 67% report receiving incorrect information about a local business from an AI recommendation.

Digging in: AI search is creating more touchpoints, diluting the accuracy of last-touch measurement if consumers encounter information on an AI platform, verify on Google or social, then convert offline.

Brands need to compete on where they rank, as well as on whether they can survive cross-platform verification. They may show up in an AI recommendation but lose the customer if hours, inventory, pricing, or reviews don’t align, highlighting the importance of underlying data quality and reputation signals.

Recommendations for marketers: With adoption growth outpacing trust, marketers need to ensure brand information and identity are consistent across the web to avoid seeming unorganized or scammy. Treat AI recommendations as the start of the discovery channel and make it easy for consumers to validate what they find through credible reviews, owned channels, social presences, and clear answers in search results.

Monitoring where referral traffic is coming from is only one part of the equation amid disconnected paths to purchase. Due to fragmentation, marketers should use KPIs such as store visits and assisted conversions to capture user journeys that span channels and measure points of influence.

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