KAB: Digitising 6 million m² with AI and a shared data foundation

KAB manages more than 6 million square metres of property across 65,000 homes. To digitalise its entire portfolio and establish a shared data foundation for maintenance planning and prioritisation, KAB has implemented proprty.ai as a core component of its digital property operations.

Challenge: From scattered data to a shared overview

With thousands of buildings spread across multiple housing organisations, KAB faced a familiar challenge. Data on building condition was scattered across Word documents, PDFs, and Excel sheets. Condition assessments varied from site to site, making it time-consuming and difficult to form a consistent overview of where maintenance needs were greatest.

As Lisa Holst, Director of Property at KAB, explains:

“When you are digitising such a large housing portfolio, it is absolutely crucial to get high-quality data into our facility management system. That’s where proprty.ai comes into the picture.”

Solution: AI and an app that create structure and integration

With proprty.ai, KAB now uses a solution that combines AI-based analysis with a user-friendly app for building inspections. The platform generates condition assessments, remaining lifetimes, and construction years for each building component, while allowing inspectors to capture photos and notes directly during site visits.

Katja Bovbjerg Hansen, Senior Consultant and Product Owner for KAB’s facility management system, Dalux FM, elaborates:

“We get a tool that provides AI-assisted condition assessments of our building components, while still allowing us to adjust and add comments in the app. This enables us to work consistently and data-driven across the entire organisation.”

The integration between proprty.ai and Dalux FM ensures that all data flows automatically between systems. Operations teams can work in a single, unified system without double work or manual imports.

Results: Faster assessments and better decisions

Already in the pilot phase, KAB completed condition assessments for an entire housing department. The AI model delivers an up-to-date and accurate view of the building portfolio, forming a strong foundation for planning, budgeting, and prioritisation.

“We spend less time on manual assessments and make more qualified decisions. It creates a shared language around maintenance and makes it easier to act based on data,” says Katja Bovbjerg Hansen.

Feedback from operational teams has been highly positive, particularly regarding the usability of the app and the quality of the AI-generated assessments.

Looking ahead: A data foundation for CO₂ reduction and future investments

Next, KAB plans to use proprty.ai as the foundation for its CO₂ reduction strategy. The AI-generated data will help identify where the greatest climate impact can be achieved through preventive maintenance rather than major renovations.

“We now have a tool that is both flexible and precise, and that will be a key component of our digital property operations,” concludes Lisa Holst.