Artificial intelligence in real estate asset management: Towards buildings that manage themselves... where are we going?

Turning buildings into data platforms enables predictive maintenance, lower costs, and embracing the digital twin while changing the developer's mindset.
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AI in real estate asset management: Towards buildings that manage themselves... where do we go?"

Hisham Alqasem

<For a long time, buildings were seen as static assets; walls, systems, and regular maintenance. But in 2025 they are becoming dynamic entities, interacting, learning, and even partially self-managing thanks to artificial intelligence.

Buildings are no longer just static assets. <The building is no longer just a residential or commercial unit, but a living data platform, recording every detail from elevator performance, electricity consumption, frequency of breakdowns, to the level of resident satisfaction.
This data, when processed using artificial intelligence tools, turns into decisions. Suddenly, the system can alert the maintenance team before the air conditioner breaks down, or suggest improvements that reduce the electricity bill by 20%.

Suddenly, the system can alert the maintenance team before the air conditioner breaks, or suggest improvements that reduce the electricity bill by 20%.

What has really changed?
  1. The role of asset management has shifted from reaction to prediction and prevention.
  2. The emergence of machine learning techniques in assessing the performance of HVAC, lighting, insulation, etc.
  3. Digital Twin to visualize and continuously improve building performance in real time.
<These shifts are opening the door to a new paradigm: »Operational Intelligent Real Estate«.
Not just in operating elevators or controlling lighting, but in making full management decisions, driven by data.

The real challenge: How do we embrace this future?"

<The question is no longer «Can we?» but «when and how?»
Start by qualifying the infrastructure to be able to capture data. Then integrate the systems into a unified platform, and choose algorithms that fit the nature of each project.

But most important of all. <But most important of all is changing the developer's mindset:
Recognize that investing in operational technology today means reducing future risks, increasing operational efficiency, and increasing asset lifespan.

Who adopts operational intelligence today?

Whoever embraces AI now...will have the competitive edge in the near future.

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@ArchHesham