The digitalization of the real estate industry is progressing slowly. Despite the huge potential offered by modern technologies such as artificial intelligence (AI) and big data, many companies are facing considerable challenges. In this article, we highlight the five biggest digitalization hurdles and show how companies can overcome them.

The general shortage of skilled workers in Germany does not stop at the real estate industry. At the end of 2023, there were around 580,000 employees subject to social insurance contributions working in the sector.¹ The structure of the companies is particularly striking: 97.24% employ just one to nine people. This small-scale corporate landscape makes the implementation of digitalization measures considerably more difficult.

According to a study by ZIA and EY Real Estate, 80% of the experts surveyed report that a lack of human resources is one of the biggest hurdles to digitalization.² 55% of those surveyed by the European Training Centre for the Housing and Real Estate Industry even see the shortage of skilled workers as an obstacle to investment. The KfW-ifo Skilled Workers Barometer also predicts that demographic change will further exacerbate the shortage of skilled workers: From 2025, the number of people in employment in Germany will begin to shrink.³

As the shortage of skilled workers will not be solved in the foreseeable future, companies must optimize their existing processes so that they can work efficiently with the available resources. Automation and digital platforms play a key role here. AI-supported systems can take over administrative tasks such as document management, data capture and reporting, freeing up valuable human resources for strategic activities.

The German real estate industry is characterized by non-transparent data structures and analogue processes. There is a lack of cross-company standards and many companies manage their data in isolated silos. According to a survey, 73% of respondents state that non-transparent data structures and a lack of data quality are one of the biggest hurdles to digitalization.²

• Complicated decision-making processes due to incomplete or incorrect data
• High manual workload for data cleansing
• Distorted forecasts due to inaccurate or non-standardized data
• Limited usability of digital tools and automation solutions

17% of the companies surveyed already use artificial intelligence to optimize existing processes, for example in document analysis. AI models can contextualize and enrich unstructured data and prepare it for further analysis. Modern large language models (LLMs) already achieve an accuracy rate of 91.8% - even higher than that of human experts (89.8%).⁴ The key to successful digitalization therefore lies in improving data quality and implementing intelligent data management systems.

Digitalization requires investment. However, many companies lack the funds or strategic understanding for targeted digital projects. A survey shows:

• 31% of companies invest more than 5% of their annual turnover in digital measures.
• 45% only invest between 1 and 5%.
• The PMRE Monitor 2024 estimates that 5.7% of turnover would have to be spent on AI solutions alone.5

Many real estate companies rely on a variety of software solutions that often only solve isolated problems. This fragmentation of the IT landscape leads to

• high license and maintenance costs
• Inefficient workflows due to incompatible systems
• unnecessary complexity in the IT infrastructure

Instead of indiscriminately investing in new software solutions, companies should develop a holistic digital strategy. This must:

• pursue clear economic goals (e.g. reducing costs, increasing efficiency)
• be measurable in terms of KPIs such as processing times and administrative costs
• Be integrated into the overall corporate strategy

Although the real estate industry fundamentally recognizes the potential of AI, there is often a lack of specialist knowledge regarding its specific implementation. A survey shows that 56% of experts state that a lack of knowledge about the possible applications in the current business model is a key barrier to digitalization.²

Potential of AI in the real estate industry

• Automated analyses: faster and more accurate property valuations
• Dynamic reporting: real-time overview of market trends and key company figures
• Efficient transaction processes: Reduction of the average transaction duration of 342 days⁶
• Increased security: Encrypted communication and secure data storage

Companies should invest in targeted training and work with specialized technology partners to identify the right AI tools for their business model.

Many companies and employees are skeptical about AI-supported solutions. This is often due to the lack of transparency of the algorithms (“black box” problem), which makes decision-making more difficult.

Technology acceptance is based on two factors:

• Perceived usefulness: does the technology lead to measurable improvements?
• Ease of use: Is it intuitive to use?

• Explainable AI: Transparent algorithms that make their decision-making processes comprehensible
• Interactive training: Involving users in digital processes in a targeted manner
• Data security: clear data protection guidelines and secure cloud infrastructures

Digitalization is not a sure-fire success. However, the biggest challenges - a shortage of skilled workers, non-transparent data structures, high costs, a lack of specialist knowledge and a lack of acceptance - can be overcome with the right strategy. Companies that make targeted investments in digital solutions and optimize their processes at the same time secure long-term competitive advantages.

Immodeal.io helps companies overcome these hurdles by combining intelligent technologies with practical application. Now is the time for a smarter real estate industry!

Sources:
1 ZIA, 2024. Die Bedeutung der Immobilienwirtschaft in Zahlen.
2 ZIA/EY Real Estate, 2024. KI – ein „Game Changer“ in der Immobilienwirtschaft?
3 Müller, Martin. 2023. KfW-ifo-Fachkräftebarometer Dezember 2023
4 Hendrycks, et al., 2020. Measuring Massive Multitask Language Understanding.
5 Peyinghaus, et al., 2024. PMRE MONITOR Spezial. Berlin : htw Berlin & CC PMRE GmbH
6 Drooms, 2024. Drooms Real Estate Transaction Barometer 2023