Entering the Era of ‘Asking AI for Property Searches’: 53.4% of People in Their 20s Use Generative AI

News Reference and Introduction

The All Japan Real Estate Federation and the Real Estate Guaranty Association have released the “2026 Housing Residence White Paper.” The survey was conducted on 5,000 men and women aged 20 to 65 nationwide. According to R.E.port, 33.9% of people have used generative AI in some form for home searching or comparing and considering properties. By age group, 53.4% of those in their 20s, 42.3% in their 30s, 31.4% in their 40s, 19.6% in their 50s, and 14.8% of those 60 and older have used it. In other words, more than half of those in their 20s already have experience using generative AI during the home-searching process. What is even more interesting is the purpose of use. Among the 1,695 people who have used generative AI, the most common reason was “collecting and comparing regional information for a desired area” at 33.5%. AI is being used not just to search for properties themselves, but to collect information to decide “where to live.” The survey also asked about expectations for real estate companies. The most common response was “clear explanations” at 21.4%, followed by “conveying all information without hiding anything, including disadvantages, not just benefits” at 19.1%, and “polite customer service” at 17.4%. While AI makes information gathering easier, it is important that real estate companies are ultimately expected to “organize information clearly and explain both the good and bad aspects.”

How are users actually using generative AI?

The characteristic of generative AI in home searching is that it is closer to “consultation” than “search.” With traditional search engines, users would enter keywords like “XX Station rental 1LDK” or “XX Station real estate agency recommendation” and check the displayed sites one by one. With generative AI, they can convey more specific conditions all at once. For example, they can ask, “Tell me five towns suitable for living alone that are within a 30-minute commute to work, under 120,000 yen in rent, have good public safety, and have supermarkets nearby.” They can also continue the conversation by asking, “Compare those five stations in terms of rent market, transportation convenience, shopping, and safety,” or “What kind of real estate agencies are there if I’m looking for a room at XX Station?” In other words, rather than replacing portal sites, generative AI is entering the “pre-stage” of looking at portal sites. There is a possibility that users will narrow down areas, conditions, and real estate agency candidates through conversations with AI before they even start searching for properties. The same applies to buying and selling. They might consult AI by asking, “If my annual income is XX yen and my own funds are XX yen, how much of a mortgage is realistic?” “Is it better to buy new or used?” “Will this area maintain its asset value in the future?” or “What about hazard risks?” and then inquire with a real estate company afterward. Cases where users have already organized a considerable amount of information using AI by the time they meet with a sales representative will likely increase.

What is the “AIO strategy” required for future real estate companies?

This is where AIO, or AI Optimization, becomes important. It is easy to understand if you think of it as an effort to create a state where your company and the information you disseminate are easily referenced and introduced when someone asks a question to generative AI. If SEO is a “measure to be found by search engines,” then AIO is a “measure to organize information so that it is easy for AI to understand and reference when creating answers.” For example, suppose a user asks a generative AI, “What real estate agencies are strong in rentals in the XX area?” or “What real estate agencies are knowledgeable about investment condominiums?” At this time, what is important is not just writing “community-based” or “customer first” on your website. It is important that your company’s location, service area, types of properties you specialize in, service details, track record, expert information, FAQs, and regional information are specifically disclosed. I believe real estate companies and AIO are particularly compatible. This is because one of the major assets that real estate companies have is “regional information.” Information such as “rent market for singles at XX Station,” “points to consider when looking for properties in the XX area,” “differences in living environments between the east and west exits of XX Station,” and “reasons why there are few properties with parking in this area” can only be disseminated by companies operating in that region. Accumulating such specific information on your own website or blog will be meaningful not only from an SEO perspective but also from an AIO perspective. Also, “who is disseminating the information” is important. By organizing not just the company profile, but also the profiles, areas of expertise, experience, and written articles of real estate agents, sales staff, and management staff, it becomes easier to understand “what this company is knowledgeable about” and “who is disseminating this information.” The specificity of information is also important. Instead of saying “we are a company knowledgeable about the region,” clearly state facts such as “operating in the XX area for 20 years,” “managing XX rental units,” “XX brokerage deals per year,” and “analyzing the rental market around XX Station every month.” Instead of saying “strong in buying and selling,” indicate which areas, price ranges, and property types you specialize in. The point is to increase information that is easy for both AI and users to understand, rather than abstract advertising slogans. Furthermore, it is not enough to just maintain your own website. It is also necessary to increase the consistency of all your company information existing on the Internet, such as store information, reviews, social media, publications in industry media, and interview articles. If basic information such as company name, address, and business description varies by medium, it will be difficult for both users and AI to grasp the company’s image.

From a “company that gets searched” to a “company that can be explained to AI”

Until now, in web customer acquisition for real estate companies, “whether you appear at the top of search results” was a major theme. However, from now on, the action of “asking AI” may come before that. The result of the All Japan Real Estate Federation survey that 53.4% of people in their 20s are already using generative AI for home searching shows that this change is not a story of the future, but has already begun. Of course, just because you implement AIO measures does not mean you will definitely be introduced by a specific generative AI. The way generative AI answers and the information sources it references differ depending on the service, and the mechanisms are constantly changing. Therefore, rather than looking for superficial “AI hacking methods,” it is important to increase accurate and specific information on the Internet. Accumulate “information that only this company can provide,” such as regional information, market prices, transaction examples, staff expertise, answers to frequently asked questions from users, and explanations that include not only benefits but also disadvantages. This will lead to SEO, AIO, and gaining trust from users. It is not enough for future real estate companies to think only about “how to use AI to improve operational efficiency.” An era has begun where users themselves use AI, and through that AI, they research towns, compare properties, and choose real estate companies. “When a user asks AI about your company’s trade area, is your company’s information being used as material for the answer?” It seems necessary to review your company’s website and information dissemination from this perspective.

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