Google representatives confirmed on September 24 that AI search is reshaping local queries into multi-part requests, and that a Google Business Profile carrying only a name and opening hours may no longer answer enough of what a customer asks.

The statements came during the webinar "Google On What's Next In AI Search + 5 Local Marketing Strategy Fixes," featuring Google's Caroline Dissaux, Adecco's Bonnie White, and Uberall's Krystal Taing. Google representatives described longer, more conversational searches and AI features that break complex requests into related questions. Taing's practical point: the familiar work of maintaining local information now has to hold up across every location.

A customer asking whether a nearby location offers a service this weekend needs more than an address. Taing said businesses should make categories, attributes, services, menus, inventory, and availability both complete and consistent across their site, Google Business Profile, and other relevant surfaces.

Consistency does not mean identical copy everywhere. It means customers and search systems should not encounter conflicting facts.

Scale, Not Novelty, Drives the Change

Taing framed the shift directly: "Most of us really have been talking about these things for years. What's different is the scale, the complexity, and importance of getting these right across every location and what it means to LLMs and generative AI." (31:19)

That distinction matters for chains. A strong brand-level presence does not establish that each branch can meet a specific request. It also makes a location-by-location data audit more useful than assuming one national profile represents every store.

What To Add To A Google Business Profile

Dissaux and White recommended concrete ways to keep Business Profile information fresh. These are content and accuracy priorities, not a guarantee that adding any single field will make a business appear in an AI answer.

Publish relevant updates, offers, and events. Google Posts can carry timely details, including event dates and offer information. Keep the cadence realistic for the business rather than copying a social-media schedule.

Connect social accounts and refresh images. Link the business's existing social profiles to its Google Business Profile, and update photos or videos when products, spaces, or seasonal details change. A brand-wide social account is still usable when a location-specific one does not exist.

Supply structured menus or detailed services where relevant. Food businesses can list menu items, ingredients, and current prices rather than relying only on a photo of a customer-uploaded menu. Service businesses should describe their offerings and relevant details in their service lists; they is no need to invent a food-style menu.

Respond to reviews and keep contact options current. Reviews can add customer-specific context that the business's own profile cannot supply. Responding also gives teams a chance to learn which experiences or offerings need clarification. Where appropriate, make the available messaging channel easy to find.

Measurement Questions From The Audience

In the Q&A, Taing said Google Business Profile post views and clicks can now help teams assess individual posts — but those figures do not establish that a post caused visibility in AI Overviews or AI Mode. This is a tool-signal limitation worth noting: Google offers engagement data, not attribution. She suggested comparing post topics with the queries and AI answers a business actually sees. Dissaux cautioned that there is no clear-cut metric tying posts directly to AI visibility.

For brands posting across many locations, the speakers said the same promotion can technically be reused, but local details make it more useful to a person deciding where to go. They also advised adding prices only when the business can keep them accurate; a service with variable pricing may be better described clearly without an unreliable figure.

The full on-demand webinar walks through Google Business Profile examples and Uberall's approach to scaling these checks. Its most useful takeaway for multi-location teams is not to add every field at once, but to give each location an owner, a source of truth, and a way to detect gaps.

Five Fixes To Put Into Practice

Automation can help a central team handle the volume, but Taing argued that people still have to decide the standards and exceptions: "It doesn't mean that a human needs to manually review every single thing. You know, you can have models, you can have these elements, but it does mean that humans should be the ones establishing the strategy, the standards, the guardrails." (38:29)

That division of labor turns the session into a practical sequence:

1. Establish one source of truth for each location. Audit hours, categories, attributes, services, menus, inventory, and booking details; fix conflicts before syndicating updates.
2. Close the review gap. Set ownership and response standards, then use recurring customer feedback to identify missing information and location-specific problems.
3. Localize content at scale. Reuse approved offers where appropriate, but add accurate neighborhood, service, image, or location details instead of distributing generic copy alone.
4. Automate with human judgment. Let systems flag missing fields and routine updates; require human review for policy, brand-sensitive claims, unusual complaints, and exceptions.
5. Measure at the location level. Track a consistent set of customer questions and AI answers for individual locations and competitors, then compare those observations with profile engagement and actual business outcomes over time.

For multi-location brands, the near-term signal to monitor is whether Google introduces clearer attribution between Business Profile activity and appearance in AI Overviews and AI Mode — until then, the speakers' guidance stands: compare post topics against the queries and AI answers your business actually receives.