Artificial Intelligence (AI) has achieved a significant presence in the real estate industry. A joint survey by aedifion and Rueckerconsult among 35 companies in the sector shows that 86 percent of respondents already use AI applications. Of these users, 90 percent utilise generative systems such as ChatGPT, Claude, Gemini or Perplexity. The results of this survey were presented and discussed during an online press conference titled “AI in Reality Check – How Far is the Real Estate Industry?”. Participants included Dr.-Ing. Johannes Fütterer, CEO of aedifion, Prof. Dr. Kunibert Lennerts, Professor of Facility Management at the Karlsruhe Institute of Technology (KIT), and Thomas Wiese, Technical Property Manager at B&L Property Management.
Despite the widespread adoption of individual applications, the systematic integration of AI into company and building processes is still lacking in many areas. Only 27 percent of companies use integrated AI platforms that can access their own data sources. The current application of AI primarily focuses on administrative processes; 70 percent of AI users employ the technology in areas such as accounting, document management or translations. Strategic analyses, including portfolio analyses, market research and ESG reporting, are supported by AI by 60 percent of users. In contrast, AI is currently only used by 23 percent of users in operational building control, for example for energy management, predictive maintenance or system regulation.
Dr.-Ing. Johannes Fütterer from aedifion emphasised that the current readiness of the industry is still very varied, but awareness of the need for process and business model changes has grown considerably. He sees great potential for efficiency gains, particularly in asset and property management, through data structuring and the intelligent linking of systems, as a significant portion of daily work involves information and data exchange. Respondents confirm the concrete benefits of AI: 90 percent report measurable time savings, 43 percent were able to reduce costs, and 30 percent each cite better data quality and improved decision-making as advantages. New business models or services through AI have only emerged in 17 percent of companies.
Challenges in Data Availability and Strategic Integration
Prof. Dr. Kunibert Lennerts from KIT points out that individual time savings through AI have not yet automatically translated into more efficient corporate processes. Many users simplify their daily work through applications such as ChatGPT, but the next step is providing the necessary data and changing organisations so that AI optimises entire processes. Only then could AI agents independently take on structured tasks. The companies' objectives underpin the current focus on efficiency: 90 percent of AI users aim for resource savings, 77 percent want to create better analyses and decision-making bases, and 67 percent aim to improve service quality. Process automation is mentioned by 50 percent, innovation and idea generation by 43 percent.
Another challenge is the data foundation. Currently, companies primarily rely on market and transaction data (57 percent), public sources and web data (53 percent), and internal company data (50 percent) for AI-supported processes. Building-related data is used significantly less frequently: technical operating data is used by 20 percent, sensor data and ESG and sustainability data by 17 percent each. Nevertheless, their importance is recognised; 63 percent consider real-time building data important or very important for AI-supported decisions. This represents significant, largely untapped potential, particularly for building operations. Expectations include lower operating costs (63 percent), better lettability (60 percent), a longer lifespan for technical systems (37 percent), and value appreciation (33 percent).
Thomas Wiese from B&L Property Management sees a need for development in practical application, especially regarding the provision of live data from properties. The manual collection of much information from maintenance, inspections or operation involves considerable effort. Here, AI could make a significant contribution to evaluation, to more quickly identify the condition of a property, the development of energy consumption and the need for action. In addition to data availability, governance is a crucial prerequisite for the next stage of development. Although 40 percent of companies already have an AI policy, and another 30 percent are developing such rules, a dedicated budget for AI is only available in 27 percent. This carries the risk that employees, in the absence of secure corporate solutions, may resort to publicly available applications and process sensitive data there.
