The Winner in AI Search Wasn't the Store: 5-Industry Survey Reveals the Era of Industry Infrastructure Dominating Recommendations

Launch of the Agent Readiness Index™ (ARI)

5

25

231

Over 3,000

Claude Sonnet

Targeted Industries

Number of Queries

AI Responses Analyzed

Brand Mentions Analyzed

Phase 1 Targets

This is Japan's first quantitative comparative study (by our company) on industry-specific brand recommendation rates in AI search. We observed up to a 5.5x gap in recommendation rates across industries. Industries with higher AI recommendation rates tend to have well-established comparison, reservation, and information infrastructure, suggesting that the competitive landscape of AI search is shifting from individual stores to the industry infrastructure layer.

With the widespread adoption of generative AI, businesses and stores are entering an era where it's no longer enough to be 'found'—they must also be 'recommended by AI.' Core Retail LLC (Minato City, Tokyo; Representative Partner: Kenno Sasaki, hereafter 'Core Retail') conducted an original survey using Claude Sonnet to examine which brands are recommended by AI across five industries: dentistry, beauty, fitness, real estate, and professional services. The results showed that brand recommendations occurred in 97.8% of queries in real estate, compared to only 17.8% in dentistry and 15.6% in professional services. Furthermore, industries with higher recommendation rates tend to have abundant comparable information, established reservation pathways, and machine-readable data. This suggests that AI search competition may be influenced not only by individual stores' SEO strategies but also by the design of industry infrastructure, including reservation systems, CRM, POS, and industry-specific SaaS.

Key Finding ① — Up to 5.5x Industry Gap in AI Brand Recommendation Rates

Core Insight of This Survey

The winner in AI search is not the store. We are entering an era where industry infrastructure dominates recommendations.

Industries with higher AI recommendation rates tend to have well-developed reservation, comparison, and information infrastructure. This suggests that information infrastructure—such as reservation systems, POS, CRM, and industry SaaS—may influence AI recommendations. If AI agent-driven booking completion becomes widespread, industry infrastructure providers could become gateways for AI-driven customer acquisition. (Note: This survey observes correlation, not causation.)

We confirmed significant differences in competitive structures across industries in AI search. In real estate, brands are recommended in nearly all queries, while in dentistry and professional services, AI completes responses using general information in over 80% of cases.

Key Finding ② — AI Recommendations Tend to Concentrate on a Few Brands

In industries where recommendations occur, concentration on a few brands is evident. In real estate, SUUMO captured 47.7% of recommendations, while in fitness, zen place pilatés accounted for 48.6%. The competitive advantage of being on the 'recommended side' in the AI agent era is already at a high level.

Key Finding ③ — Common Trends in Industries with High AI Recommendation Rates

Common trends in high-recommendation-rate industries:

- Abundant comparable information - Established reservation pathways - Unified brand information - Machine-readable data availability

Common trends in low-recommendation-rate industries:

- High reliance on qualitative factors such as staff skill, compatibility, and confidentiality, making AI cautious about recommending specific providers - Possible impact of insufficient structured data and lack of online reservation infrastructure on AI recommendation frequency

⚠️ This survey confirms correlations but does not establish causation for industry disparities. The hypothesis that 'information infrastructure readiness' causes AI recommendations requires further investigation through ongoing studies.

Hypothesis Derived from This Survey — The Main Battleground of AI Search Shifts from Stores to Industry Infrastructure

Hypothesis — Changing Competitive Structure in the AI Era

Store-level AI strategies may face structural limitations. The key may lie in industry infrastructure.

This survey confirmed that industries with higher AI recommendation rates tend to have abundant comparable information, established reservation pathways, and structured data. This trend cannot be explained solely by individual stores' brand recognition or content volume, suggesting that the design of information infrastructure—including reservation systems, POS, CRM, and industry SaaS—may influence AI recommendations.

Future Outlook

If AI agent-driven booking completion becomes commonplace, the main players in AI-driven customer acquisition competition may shift from individual stores to industry infrastructure providers. Companies with industry-wide platforms—such as hacomono, Reservia, STRANZA, medicalforce, and GMO Beauty—could elevate the AI competitiveness of all connected stores by advancing Agent Readiness integration.

※ The above is a hypothesis based on observational results from this survey and does not establish causation.

Evolution of Customer Acquisition in the AI Search Era — From SEO to Agent Readiness

SEO (visible to search engines) → GEO (cited by generative AI) → Agent Readiness (recommended and executed by AI agents)

We believe we are currently in a transition phase toward the third stage.

What matters is no longer just 'being found,' but ensuring AI can compare, select, and complete reservations.

Initiatives Based on This Survey — Launch of the Agent Readiness Index™ (ARI)

Core Retail LLC announces the launch of the 'Agent Readiness Index™ (ARI),' an evaluation metric that visualizes readiness for AI agents, based on this survey.

Details and scoring criteria: ▶ https://www.coaretail.com/readiness

Launch of Vendor Collaboration Program

The biggest insight from this survey is the possibility that industry infrastructure underpins AI recommendations. Therefore, we are launching an Agent Readiness Collaboration Program for vendors providing reservation systems, CRM, POS, and industry SaaS. By enabling vendors to support Agent Readiness, we aim to enhance the AI competitiveness of all connected stores. ※ API integration and white-label solutions are planned for the future.

Future Developments

Executive Comment

What we saw in this survey is that the competitive structure of AI search itself is beginning to change.

Until now, the key was appearing in search results. But in the AI agent era, businesses must be comparable, selectable, and bookable. The difference is not in content volume—it's in information structure.

And that information structure may be supported not by individual stores, but by industry infrastructure. Through the Agent Readiness Index™, we will visualize how prepared businesses and stores are for the AI era and provide actionable improvement guidelines.

Kenno Sasaki, Representative Partner, Core Retail LLC

※ Agent Readiness Index™ is an evaluation metric proposed and operated by Core Retail LLC. ※ AI Search Visibility Survey 2026 (Preliminary Report) targets Claude Sonnet (Anthropic) in June 2026