Core Viewpoint - The article emphasizes the critical role of artificial intelligence (AI) in driving innovation and transformation within the real estate industry, highlighting the need for collaboration and the establishment of industry standards to facilitate AI integration and application [2][4][5]. Group 1: AI Application Development - 2025 is identified as a pivotal year for the explosion of AI technology, with significant advancements in foundational models and various intelligent applications [3]. - The report by the CEO of Ke Rui Group outlines the current state, challenges, and future trends of AI applications in the real estate sector, based on extensive research of leading real estate companies [3]. Group 2: Policy and Strategic Focus - The current period is characterized as a golden age for AI policy benefits, with the government introducing a series of "AI+" and "urban renewal" policies aimed at deepening the integration of AI with traditional industries [4][5]. - The focus of these policies is on three core areas: deep integration of AI with traditional industries, building a new framework for digital China, and achieving high-quality urban development [5]. Group 3: Investment Trends in Real Estate - During the 14th Five-Year Plan, leading real estate companies saw a peak in digital investment at 150 million yuan in 2021, followed by a decline in subsequent years, indicating a cautious approach towards AI investment despite its anticipated importance [14]. - Over 90% of leading real estate companies expect AI to be operational within 1-2 years, but only about 40% anticipate an annual growth rate of 10-30% in AI investment [14]. Group 4: AI Application Characteristics - The real estate industry exhibits a dual characteristic in AI investment, with over one-third of enterprises (mainly state-owned enterprises) investing over 10 million yuan, while most remain at the million-yuan pilot stage [19]. - Domestic large models dominate the technology selection, with an average of 2.9 models adopted to meet diverse business needs, indicating a trend towards practical and adaptable technology architecture [19]. Group 5: AI in Real Estate Lifecycle - AI applications are identified in five core business scenarios within the real estate lifecycle: investment decision-making, design and construction, marketing services, property services, and real estate operations [29][30]. - AI is transforming investment decision-making from experience-based judgments to data-driven strategies, enhancing efficiency in construction processes, and revolutionizing marketing and customer engagement [30]. Group 6: Challenges in AI Implementation - The primary challenges in AI application include technology and talent shortages, with many enterprises still evaluating the reliability of AI technologies and facing difficulties in utilizing unstructured data [22][24]. - Data silos are a significant issue, with over 70% of companies experiencing moderate to severe data isolation, hindering effective data integration and AI training [26]. Group 7: Talent Shortage and Organizational Response - A shortage of composite AI talent, particularly those who understand both business and technology, is a critical bottleneck for enterprises [28]. - Companies are actively addressing this by providing systematic AI skills training and gradually replacing repetitive roles with AI, indicating a shift towards internal transformation and external talent acquisition [28]. Group 8: Future Directions and Collaboration - The article concludes that the release of AI application value is a long-term process, requiring strategic patience and systematic implementation across various paths, including high-quality data construction and talent cultivation [59]. - Ke Rui and the China Real Estate Association's AI Application Subcommittee are collaborating to launch an industry AI application development cooperation plan, aiming to summarize and promote intelligent practices in the real estate sector [61].

Group 1: AI Strategy and Advantages - The company has developed a large model, AecGPT, specifically for the construction industry, which was released in 2024 and can pass the national construction examination with high scores [2] - Key elements for successful industrial AI include high-quality data, valuable scenarios, and reliable models [2] - The company possesses a comprehensive engineering construction knowledge base that supports the construction large model [2] Group 2: AI Application Scenarios - The company focuses on three main directions for AI scenario implementation: integrated design, refined cost management, and precise construction management [3][4] - In integrated design, AI is used to enhance design workflows and assist in construction drawing design [3] - Refined cost management leverages AI and data to drive detailed cost management throughout the project lifecycle [4] Group 3: Value Measurement and Commercialization - High-value AI applications should be able to deliver a complete task process, be measurable in value, and continuously learn and optimize [5] - The AI intelligent bidding product has been implemented in 716 construction bidding projects in Hainan, resulting in an average bid reduction rate of 8% and saving approximately CNY 4.56 billion [5] - The commercial value of AI products is closely linked to technological maturity and the ability to meet new demands [6] Group 4: Future AI Opportunities - Future high-value AI scenarios will emerge from both technological breakthroughs and evolving market demands [7] - The upcoming market reforms in September 2025 will drive the need for effective data management and cost control in the construction industry [7] - The company is developing an automatic database construction product that will enhance data collection and analysis efficiency [7]

Investment Rating - The report maintains a "Recommended" rating for the company [6][8]. Core Insights - The company's core business is steadily developing, with significant performance improvement expected in 2024. The digital cost business is evolving from single-position tools to comprehensive cost application scenarios, while the gross profit margin is rising and expenses are being optimized, leading to a rapid recovery in net profit [3][15]. - Policies are expected to boost downstream market conditions, with the SaaS leader poised to embark on a new growth journey. The support for the real estate market is anticipated to enhance downstream information technology spending [4][21]. - The company is comprehensively laying out AI models and applications, integrating deep industry understanding with intelligent technology. The AI capabilities are expected to significantly enhance operational efficiency and decision-making accuracy [5][30]. Summary by Sections 1. Core Business Development and Performance Improvement - The digital cost business is transitioning to full-process applications, with stable renewal and application rates for traditional cost tools. The number of application projects in the digital design business has increased to 1,440 [3][13]. - The company expects a net profit of 250 million yuan in 2024, a year-on-year increase of 116.19%, with a non-recurring net profit of 174 million yuan, up 219.92% [15][39]. 2. Policy Support and SaaS Business Growth - In September 2024, the People's Bank of China and the National Financial Regulatory Administration introduced four financial support policies for real estate, which are expected to stabilize the market [21][22]. - The company's SaaS business maintains a gross profit margin above 90%, with improvements in the construction business gross margin expected in 2024 [24][23]. 3. AI Model and Application Integration - The company has launched the AecGPT AI model and various specialized models covering seven fields, enhancing efficiency in construction project management [5][30]. - AI capabilities have improved the accuracy of cost estimation products to approximately 70%, and the efficiency of design solutions has increased by 50% [36][32]. 4. Investment Recommendations - The company is recognized as a leading digital construction platform service provider, with a projected net profit of 450 million yuan in 2025, 663 million yuan in 2026, and 835 million yuan in 2027, corresponding to PE ratios of 50X, 34X, and 27X respectively [39][41].