At the 2025 Global Developer Pioneer Summit (GDPS2025) Real Estate Industry Artificial Intelligence Conference, Sun Xiaozhen, National Managing Partner of Digital & Intelligent Engineering Services at Deloitte China, said in his speech that artificial intelligence is currently attracting huge investments and is the most widely-interested topic in the world. On the other hand, there is a lot of debate about whether artificial intelligence is a bubble. Deloitte conducts a quarterly survey of 2,400 customers around the world on real-world implementations of AI applications. Although some companies have reported that their investments in artificial intelligence have not yielded the expected returns, no company has stopped continuing to invest in artificial intelligence due to this gap. In fact, they give it more importance. There are four important characteristics.
First, companies are recognizing that the pace of technology development does not determine the speed at which artificial intelligence impacts the company. Although the development of artificial intelligence technology, large model technology, and agent technology is very fast, the speed of AI applications in enterprises depends on the speed of transformation of the enterprises themselves.
Second, the emphasis is on the important role of artificial intelligence in enterprises. In the early stages, companies will apply artificial intelligence to areas that are relatively easy to implement. However, in order to transform artificial intelligence into “AI+”, application to core business is the key.
Third, there is a general lack of awareness of artificial intelligence risk management. This is important for applying artificial intelligence not only within the enterprise but also upstream and downstream of the business. Comprehensive assessment and management of AI risks is critical when delivering to consumers and partners.
Fourth, businesses are facing a transformation in their roles. Not only will the composition of a company's future human resources change, but more importantly, the management team will also change. Management's attitude toward artificial intelligence will determine the intensity and speed of AI development.
Sun Xiaozhen believes that for the real estate industry, enterprise AI transformation has not yet reached the maturity stage. In the future, more companies will need to implement AI applications in their core areas. There are five big trends right now:
- Domestic real estate companies tend to prioritize localization and cost-effectiveness when selecting technology. There is no right or wrong here. It simply reflects the current situation.
- Currently, the most common application scenarios are in the marketing phase, where the value is relatively obvious and direct. At the engineering stage, most applications are for predictive maintenance, where opportunities are primarily considered in the safety and protection aspects.
- The deployment architecture is primarily private.
- Although the agent is widely recognized, it is still in its infancy in terms of the depth of its application. However, this does not mean that no company achieves thorough application of agents. For example, Shendu Zhilian can generate a 30,000 word report. The length of the report indicates that it involves not just one agent but multiple agents and requires a great deal of cooperation.
- The biggest obstacle to implementing AI in the real estate industry is data quality. This is not just a challenge for individual companies, but a common challenge that the entire real estate industry will face over the next one to two years.
In the future, these five trends are likely to change during the development of artificial intelligence in the real estate industry, including the current deployment and scenario selection. Once a leading application gains influence and a small number of good application cases emerge, there will be a very positive follow-up effect.
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At the critical moment of the industry's transformation from traditional development experience to the AI technology era, Shendu Zhilian officially launched the “Real Estate AI – Ready” strategy and systematically introduced the “AI – Dedicated Space” based on “four core libraries” and a complete product portfolio covering three types of business scenarios. For the first time, we presented a systematic solution: “One dedicated space, four core functions, and three tiers of application scenarios.” This indicates that the intelligentization process of the real estate industry has officially entered the “ready” stage of full-chain and systematic deployment and provision from the decentralized “tool-empowerment” stage. At the same time, it provides a viable path for intelligent upgrading of the real estate industry.
By building four core capabilities: data asset management, intelligent decision support, process automation, and knowledge intelligence, Shendu Zhilian will help enterprises achieve deep integration of AI in key areas such as marketing, engineering, and operations, accelerate the industry's transformation from experience-driven to data-driven and algorithm-driven, and accelerate entry into a new phase of intelligent collaboration in the critical year of 2025.
Shendu Zhilian officially launches “Real Estate AI – Ready” strategy
Currently, Shendu Zhilian is tailoring its product features to the industry's most realistic application scenarios and benchmarking them against intermediate and high-level professional competency standards.
In horizontal comparison with general and vertical AI platforms, Shendu Zhilian shows significant advantages in terms of depth of knowledge, breadth of data, insurance coverage, and scenario application capabilities in the real estate field. When comparing job capabilities vertically, the company's core product portfolio typically reaches the level of mid- and senior-level employees in the industry. Products such as “CRIC Decision Expert” can handle specialized tasks of the same complexity as a director (L4).
Shendu Zhilian builds an exclusive AI space for the real estate industry with four core capabilities: database, knowledge base, expert base, and engineering capability base.
- Datamote: Systematically upgrading the massive, multi-dimensional data that CRIC has accumulated over the past 20 years into a “systematically structured database” that can be read by AI large models, providing reliable “data fuel” for all intelligent decision-making.
- Knowledge moat: Transform unstructured knowledge into a traceable, verifiable, and inferable “martial arts manual for the industry” and ensure that all AI output is “real estate jargon.”
- Industry Moat: This is the most revolutionary part. By encoding the thinking of experts into models, we infuse AI with the thinking models and decision logic of top experts, inheriting expert wisdom at scale and enabling AI to understand business at an expert level.
- Technology Moat: Ensuring that cutting-edge AI capabilities, such as the Agentic architecture introduced in April of this year, are stably and efficiently integrated into specific products. This encapsulates the ability to bridge the “last mile” from model to scenario with AI-native capabilities.
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Shendu Zhilian also announced a full series of eight products based on the AI-dedicated space, covering three major application scenarios in the real estate industry. These include “CRIC2025,'' which uses AI to rebuild decision-making and consulting business models, “CRIC Digital Employees,'' which promotes the intelligentization of real estate companies' human resources structures, and “CRIC Good Housing Review Network,'' a new type of media platform that uses AI to discover and promote high-quality Chinese housing.
- Rebuild decision-making and consulting workflows, from “providing data” to “providing results”
AI-native real estate investment decision-making platform CRIC2025, Asian real estate finance and RWA and REIT vertical AI investment advisory platform DeepHouse, and Silver Haird Digital Intelligence, the first vertical AI data intelligent platform for the elderly care industry, together form Shendu Zhilian's industry intelligent decision-making application portfolio. They all share the same feature: modifying the traditional “query data + manual analysis” model. These allow users to get answers to both “data-related” and “knowledge-related” questions through natural conversations, automatically plan workflows, independently invoke data and knowledge, and use intelligent agent tools to complete complex tasks such as providing detailed analytical reports.
- A revolution in human-machine collaboration that will reshape tomorrow's organizations
After one year of intensive training, the first group of Shendu Zhilian's real estate department “CRIC • Digital employees” officially started working. They are “decision experts” who can help complete tasks such as market analysis, strategic evaluation, and trend forecasting. “Private – Domain Editor-in-Chief” who can write marketing copy and professional articles. “AI Sales Champion” is a real estate marketer's right-hand assistant. The “Gold Medal Sales Field Team” has roots in the new home sales field and automatically completes multiple tasks such as market monitoring, customer reception, marketing decision making, and private domain promotion. These digital employees taking up their positions will mean the formation of a new organizational form of efficient collaboration between “human + digital employees” in the real estate industry. In the future, the positions, personnel composition, and management models of real estate companies will also change.
- Discover and promote high-quality housing in China using AI and build real estate brand assets in the GEO era
The CRIC Quality Housing Review Network uses AI to rebuild the traditional property evaluation, search, and recommendation model, allowing home buyers to provide a professional and intelligent one-stop service for home purchasing and home selection through natural Q&A in a variety of situations, such as checking locations, reading reviews, and comparing listings. Effectively reaching homebuyers, customizing solutions to meet users' needs, and building trust in AI in the GEO era are top priorities for marketing real estate companies. Based on this, “CRIC – Quality Housing Evaluation Network” will become a new type of media platform that supports real estate businesses in building brand assets in the GEO era.
Shendu Gillian
It is worth noting that at the morning's on-site AI tool practical workshop, the Shanghai real estate marketers who attended jointly launched the “CRIC Quality Housing Review Network.'' In just a few hours, an evaluation report of 276 properties for sale in Shanghai was created, and a “Good Housing Neighborhood Champion List'' and “Good Housing Multidimensional PK List'' based on professional AI evaluation were also released.
Meanwhile, Shendu Zhilian announced these lists at the conference and assured the entire industry and a large number of home-buying users that they will never be commercialized in the future.
Zhong Junhao, secretary general of the Shanghai Artificial Intelligence Industry Association, said the transition from discussion of “what AI can do” to practice of “what AI is doing” is happening faster than expected. Not so long ago, a related test of AI tools in the real estate sector was carried out within the industry. In some specific scenarios, their performance is sufficient to partially replace existing professional positions. This is not an alarming statement, but a true reflection of the productivity leaps brought about by advances in technology. Currently, existing industry players are already located on the industrial side, forming a complete commercial closed loop for all industries, with positive cash flows and profits, and sufficient to support continued investment in current technologies. The real opportunities presented by artificial intelligence lie in existing industrial sectors. The overall take-off and transformation of technology will only be possible if everyone accepts artificial intelligence technology. New eras are always realized through the two-way interaction of technology and industry, and today we stand at the crossroads of that historical transformation.
