AI has gained enormous prominence in the news over the past couple of years but its use for commercial property management goes back at least a decade.

Predictive AI, which uses machine learning and data algorithms to anticipate future events or needs has been instrumental in enabling property managers to monitor and control buildings and the environments within them in real time, facilitating more efficient operations.

Whether it’s flagging equipment that’s likely to malfunction, adjusting lighting based on occupancy or detecting unusual activity, it has allowed those in charge of building operations to automate numerous (often tedious) aspects of their work. While an undeniably helpful tool, predictive AI remained heavily reliant on human agency. Its key role, up until recently, has been confined to detecting and warning users about potential or existing issues, not solving them, leaving thousands of decisions, big and small, at the discretion of facilities managers. But that is set to change.

The shift from prediction to prescription

In the context of building management, we are witnessing a dramatic shift from smart to sentient buildings, run by context-aware intelligence; buildings that perceive, interpret, and act dynamically within their environment.

This shift from predictive to prescriptive AI is redefining what optimisation looks like. There was a time when having access to dashboards that provide an overview of building systems performance 24/7 was considered the pinnacle of progress. But does simply having that information automatically translate into changes in behaviour? While many buildings are currently meeting the minimum legal requirements for energy efficiency, such as an Energy Performance Certificate (EPC) rating of 'E', a much larger number will be unable to meet stricter future requirements by 2030. So, what is the value of these insights if they are not acted upon?

In energy management, for example, many reporting tools omit crucial indicators, such as energy usage from plug power, which accounts for 40% of a building’s energy use. That’s a real missed opportunity for performance gains and savings, but thanks to the new wave of AI advances, that gap can be successfully bridged.

AI that acts, not just advises

Today’s buildings can continuously track their own state, occupancy, energy use, and environment, enabling autonomous decisions that actively optimise performance. And when something’s wasting energy, the system doesn’t just raise a flag. It acts.

Sentient buildings are quickly becoming essential parts of organisational ecosystems. By integrating with enterprise platforms, they help align environmental conditions with business objectives, optimise energy during peak pricing, support hybrid work patterns, and even contribute data to ESG reporting frameworks. This marks their evolution from passive infrastructure to strategic assets. The trend is set to accelerate, and organisations and professionals that fail to adapt risk falling behind.

What this means for facilities managers

The arrival of such technology is good news for asset managers and occupiers. But what does this increase in AI autonomy mean for facilities managers and the future of their jobs?

Prior to this AI leap, facilities managers were responsible for monitoring systems and fixing issues as they occurred. Today, when many decisions can be outsourced to AI, their focus will need to shift to strategic oversight, policy setting and exception handling.

The shift from maintenance and monitoring to strategic direction will in many cases necessitate upskilling. Facilities managers in the era of prescriptive AI will need to be even more comfortable with data to interpret algorithmic outputs and develop a solid understanding of AI systems to effectively oversee them.

As the market for real estate management-focused AI solutions keeps growing, analytical thinking and commercial awareness will also be more important than ever. Finally, there will inevitably be a degree of change management as occupiers learn to coexist with AI-powered systems, bringing with it the need to educate building users about best practices to ensure desired outcomes are achieved without unnecessary friction.

The road ahead

AI continues to evolve and its use in commercial real estate will continue to deepen and broaden.

The past decade has seen a giant leap from predictive to prescriptive AI, bringing with it greater insights and allowing those previously in charge of building systems to delegate important maintenance activities.

Facilities managers are here to stay, but their skillsets are set to expand if they are to become the champions of the quiet optimisation revolution we’re currently undergoing.