A tenant reports damage via email. At the same time, tenancy agreements need to be reviewed, energy consumption analysed, investment decisions prepared and market values updated. What at first glance appear to be completely different tasks often have one thing in common: many of these processes can now be supported or partially automated using artificial intelligence.
This is precisely why many companies are finding it increasingly difficult to keep track of things. As part of the white paper ‘AI in Real Estate’, 55 AI solutions from 51 providers were analysed and grouped into 24 overarching use cases. The examples show that AI is no longer limited to individual pilot projects, but is being deployed throughout the entire real estate lifecycle.
Which use cases are actually relevant to a company depends on its specific challenges, the data available and its strategic objectives. The following examples are therefore not intended to be a ranking. Rather, they illustrate where AI is already creating tangible added value today.
From planning to operation
AI applications are now found in almost every phase of the property lifecycle. Some support the planning and development of new projects, whilst others assist with marketing, transactions or the operation of existing properties. A particularly large number of solutions today focus on the utilisation and operational phases, where large volumes of data and recurring processes create ideal conditions for the use of AI.
1. Automatically understanding and processing documents
Contracts, expert reports, specifications, minutes and technical documentation are part of everyday life in the sector. AI solutions can automatically capture, analyse and structure such documents, and extract relevant information.
Virtually all roles across the property lifecycle benefit from this. The main advantage is that time-consuming manual checking and data entry tasks are reduced and information is available more quickly. Document processing is therefore one of the most accessible entry points for AI.
2. Automated property valuation
Property valuations are based on a wide range of factors. Market information, property characteristics, location data and comparative values must be taken into account on an ongoing basis.
AI-powered valuation models help to efficiently analyse large volumes of data and regularly update valuations. This creates new opportunities, particularly for property owners, investors and asset managers, to identify developments within their portfolios more quickly and assess them more thoroughly.
3. Reviewing contracts more effectively
The analysis of tenancy, planning, construction or service contracts ties up considerable resources. AI applications can automatically structure and summarise contract content, and highlight critical clauses or risks.
Precisely because contracts play a role in almost every phase of the lifecycle, this use case is one of the most universal applications of AI in the industry. At the same time, such a use case can often be piloted relatively quickly and integrated into existing processes.
4. Optimising building services systems
Heating, ventilation, cooling and lighting systems generate large amounts of operational data every day. AI can continuously analyse this information and identify opportunities for optimisation.
This makes it possible to reduce energy consumption, improve operational processes and deploy resources more effectively. For FM service providers and property managers, this use case is now one of the most mature areas of application for AI.
5. Planning decarbonisation more strategically
For many property owners and portfolio managers, reducing CO₂ emissions has now become one of the most important strategic issues.
AI helps to systematically analyse portfolios, identify potential savings and compare different measures. This provides a more sound basis for decision-making regarding refurbishments, investments and long-term decarbonisation pathways.
6. Supporting planning and project development
Even in the early stages of a project, AI can help to compare options, develop designs or evaluate site information.
The main benefit lies in the fact that different scenarios can be analysed more quickly and planning decisions can be prepared on a more sound basis. As many of a building's costs and quality aspects are determined as early as the planning phase, the potential in this phase of the life cycle is particularly great.
What successful AI applications have in common
The examples differ significantly from one another in terms of content and objectives. Nevertheless, certain common patterns emerge. Successful AI applications are based on available data, tackle recurring tasks and deliver tangible benefits for users. This is precisely why the focus is not on individual technologies, but on the specific problem to be solved.
AI has long since become part of everyday life in the real estate sector
The market analysis shows one thing above all: AI is no longer a vision of the future in the construction and real estate industries. Throughout the entire real estate lifecycle, new applications are emerging that speed up processes, support decision-making or improve the quality of results.
However, which of these opportunities are relevant to your own company depends heavily on your individual challenges and objectives. This white paper provides an overview of all 24 identified use cases and offers guidance in a market that is currently evolving at a rapid pace.
This article is based on the white paper ‘AI in Real Estate’ by pom+Consulting AG (August 2025), which analyses 55 AI solutions from 51 providers in the construction and property sectors. (available in German)