What our specialist AI reveals about the Danish Armed Forces building portfolio

We analyzed the Danish Ministry of Defense's building portfolio with proprty.ai's specialized AI model — developed specifically to assess the condition of buildings and plan maintenance.

The analysis covers about 800 of the 4,000 buildings owned by Defence in the Register of Ownership. Here we can draw on public data sources such as BBR, DAR, energy labels and oblique photos. The result is a detailed and objective overview of upcoming maintenance needs — and the scale is significant.

Here's what we found when we ran Armed Forces properties through our system.

Overview of 800 buildings with AI

Defence is special because there are many buildings that do not contain information in public records — it makes good sense, we think. On the total 774 buildings, data exists on, predicts proprty.ai the following maintenance needs over the next 10 years:

• 90 roof replacements
• Over 100 window replacements
• 98 façade renovations
• Over 200 water and heating systemsto be replaced
• 100 Well and Drainage Renovations

We estimate that, overall, the Armed Forces will need to invest about 2.25 billion DKK. And if you make a simple linear calculation of the remaining 80%, the defense will have to invest the entire 11.25bn. DKK over the next 10 years in both corrective and preventive maintenance. Added to this is a complexity in materials and construction site for the defence buildings, which is likely to increase the budget further.

According to Danmarks Radio has previously been allocated 2.6 billion DKK between 2018 - 2023, which according to proprty.ai's predictions are not enough to deal with the backlog on the Armed Forces buildings.

A public reminder -- and the reason for the analysis

In light of the recent Criticism from the State Auditors We chose to illustrate what a data-driven approach could have made possible — not just in identifying needs, but in supporting better planning and maintenance over time.

The state auditors criticised the Ministry of Defence for lack of overview and the absence of a long-term strategy. According to the report:

• 80% of buildings have not been seen on time
• 800 million DKK in earmarked maintenance funds has not been spent
• Several facilities have serious problems like mold and run-down installations

So the challenge is not just about money — it's about having access to the right data. That's exactly it, proprty.ai It is built to deliver.

This is how the model works

proprty.ai's platform combines data from government sources -- including BBR, DAR, OIS, energy labels, satellite imagery and more -- with our own AI models trained on tens of thousands of buildings and building parts. The system estimates residual life, identifies maintenance needs, and generates priority plans over 10—30 years.

For larger portfolios, this means:

• An overall overview over building condition and future needs
• Budget projection based on longevity and risk
• Data-driven prioritization of restorative vs. preventive action

Why it makes a difference

AI does not replace professional judgment -- it reinforces it. By providing structured and reliable data early in the process, proprty.ai helps operations teams and asset managers act proactively rather than reactively.

The defense's case clearly shows how costly it can be when the overview is lacking.

Do you want to see your buildings the same way?

proprty.ai works on all buildings in Denmark. Simply use an address or a CVR number to get started.

Book a demo and see how our platform can support your long-term planning — with insights tailored to your portfolio.