Artificial intelligence has arrived in the real estate industry. The central question today is no longer whether AI will transform the sector, but how it can be used in a meaningful way: Where can it create better foundations for decision-making? Which processes can be made more efficient? And what role does human expertise play when more and more data is automatically analyzed, connected, and prepared?

These were the questions at the heart of this year’s IMMO Insights by TU Wien Academy. Under the title “AI in Real Estate: From Pilot Project to Decision-Making Tool”, experts from real estate practice, technology, research, and urban development came together to discuss concrete applications, opportunities, and limitations of AI.

The common thread throughout the day: AI creates real value when it is not treated as an end in itself, but as a tool for better, faster, and more informed decisions.

From Data to Knowledge: Why AI Needs More Than Technology

The construction and real estate industry generates enormous amounts of data every day: building data, location information, market data, planning documents, appraisals, portfolio data, ESG indicators, documents, and communication data. This information often exists, but it is not always structured, comparable, or immediately usable.

This is where AI comes in. It can help identify, organize, connect, and prepare information in a way that supports decision-making. In the best case, information overload becomes filtered knowledge. Data becomes a foundation for decisions.

However, the conference also made clear that the value of AI directly depends on the quality of the underlying data. Without clean data, clear processes, and professional interpretation, AI remains just another tool — with limited strategic value.

AI does not replace experience. It extends it.

Concrete Applications Across the Real Estate Lifecycle

The presentations showed how diverse the potential applications of AI in real estate already are today.

In her keynote “Smart Buildings, Smart Decisions”, Elena Graf-Burgstaller showed how AI and digital technologies can turn buildings from mere sources of information into active instruments for control and decision-making. Smart buildings do not only provide data — they enable a new form of data-driven value creation.

Theresa Fink contributed the perspective of resilient urban and district development. Data-based urban analysis can help us better understand infrastructure, real estate, and urban spaces, and support more long-term decision-making.

Dr. Julia Reisinger demonstrated how AI, spatial reasoning, and automation can open up new possibilities in industrial and commercial construction — from planning and variant development to master planning.

The second part of the conference focused on how real estate knowledge can be made more usable. Herwig Teufelsdorfer explored how real estate portfolios can move from document chaos to a manageable, AI-supported system. Christian Schitton showed how market communication can become quantifiable intelligence. Niki Stadler provided insights into how AI can identify potential for densification and new construction within a very short time.

The range of topics made one thing clear: AI does not only affect individual areas of the real estate industry. It is changing valuation, project development, asset management, urban planning, market analysis, and building operations alike.

Between Pilot Project and Practice: Taking the Decisive Step

One of the key learnings of the day was that many organizations do not fail because of a lack of interest, but because they struggle with how to start in a meaningful way. AI projects often appear large, complex, and difficult to grasp. At the same time, the pressure to engage with data-based technologies is increasing.

IMMO Insights highlighted a pragmatic approach: not everything has to be solved at once. The perfect solution is not required from day one. What matters is identifying concrete use cases, taking first steps, gaining experience, and learning from the process.

Or, as one participant aptly put it after the event: learning comes from trying.

This thought fits the current phase of the real estate industry well. It is not about adopting AI uncritically. It is about testing it consciously, evaluating it carefully, and developing it further where it actually leads to better results.

Human Expertise Remains Key

As powerful as technological possibilities may be, the conference made clear that AI cannot be considered in isolation. Data needs to be interpreted. Results need to be placed in professional context. Decisions remain strategic and entrepreneurial tasks.

This is especially true in real estate, where investment decisions have long-term effects. Experience, contextual knowledge, and a sense of responsibility remain essential. AI can reveal patterns, calculate alternatives, and accelerate processes. But it cannot decide on its own which development is right for a location, a portfolio, or an urban district.

The future of the industry will be more data-driven. Successful organizations will be those that combine technological possibilities with professional expertise, strategic thinking, and a clear understanding of quality.

Exchange Between Research, Technology, and Real Estate Practice

IMMO Insights once again showed how valuable dialogue between research, business, and practice is. Especially with a topic such as artificial intelligence, we need spaces where concrete applications, strategic questions, and critical perspectives come together.

At TU Wien Academy, we understand continuing education as an interface between technological development, professional specialization, and real-world practice. IMMO Insights made this visible: through practice-oriented impulses, interdisciplinary discussions, and direct exchange with experts from the industry.

Thank you to all speakers, participants, and organizers for an inspiring day and for sharing valuable insights.

With contributions and perspectives from, among others, Elena Graf-Burgstaller, Theresa Fink, Dr. Julia Reisinger, Herwig Teufelsdorfer, Christian Schitton, Niki Stadler, Bob Martens, Filiz Siber-Schmied, Gerald Franz Prucher, Wolfgang Wegmayer, and Karin Schmidt-Mitscher.

Conclusion

AI will not transform the real estate industry overnight. But it is already changing how data is used, how decisions are prepared, and how potential is identified.

The decisive step is not to follow every new technology immediately. What matters is asking the right questions: What data do we have? Which decisions do we want to improve? Which processes can we meaningfully support? And where do we still need human experience, responsibility, and strategic thinking?

IMMO Insights 2026 showed that the future of real estate will be data-driven. But it will remain a question of expertise, quality, and the courage to experiment.