Navigating AI in FM

Steve McGregor, Group Managing Director for DMA, discusses AI’s positives and pitfalls, advocating a cohesive approach between human and machine to benefit FM companies and their customers

AI is not without its shortcomings, however, and to prepare for AI, the FM industry must address several key challenges: from data issues to ethical concerns.

CHECK THE DATA

AI is only as good as the data it’s provided with. To deliver accurate insights, it needs a large amount of quality information, so where data shortages occur, poor machine learning outcomes will follow and consequent misleading results.

To counter this issue, FM companies must invest in data collection and management, ensuring AI systems are properly trained on robust and representative datasets.

AI in this context can also be good for continued learning, i.e. automatically spotting trends in system operations, for example, adjusting and improving working practices. Be warned, however, while AI can deliver impressive outputs, it lacks the human ability to contextualise information. For example, an AI system might identify a pattern of energy consumption in a building, but it won’t necessarily understand the nuances of why that pattern exists.

FM professionals need to interpret AI results within the specific context of each building or facility, using AI as a supporting tool rather than a definitive decision-maker.

FM SYSTEMS THAT AREN’T AI-COMPATIBLE (YET)

Many FM mechanisms, in particular legacy systems, were not designed with AI in mind, posing significant integration challenges. As a result, these outdated systems may limit the effectiveness of AI solutions.

For AI to be fully integrated, FM companies may need to upgrade their existing infrastructure or adopt flexible systems that can accommodate AI technologies. Where systems need upgrading anyway, consider how they could interact with AI if not now, in the future.

GOOD CUSTOMER SERVICE NEEDS A HUMAN TOUCH

While AI can optimise processes, it lacks the personal touch that customers often expect. FM is a service-oriented industry where customer interaction is crucial, and the human element remains irreplaceable. Organisations must balance AI adoption with the need to maintain positive human relationships.

AI is great for background tasks, like scheduling or predictive maintenance, and can free up time so FMs can focus on ensuring customers feel valued and understood.

WHO PAYS FOR AI?

An age-old problem, customers want the latest technologies, but they don’t want to pay for it. Transformative AI implementation comes with a significant price tag, and as outlined in this article, it’s not just the AI itself that requires investment – specialist skills may be needed, systems may need updating, staff will need training, data input and analysis must be on point. FM companies, therefore, face the challenge of determining how to finance these expenses and who should bear the cost.

In an ideal scenario, FMs have the kind of relationship with their customers where this cost can be shared, and the AI journey is embarked on together. In reality, this is often not the case. Decisions around AI investment, therefore, must weigh potential productivity gains against upfront costs.

THE ETHICS OF AI

The integration of AI raises ethical questions about data privacy, bias, and accountability. FM companies must consider how AI might impact employees’ roles and whether AI could inadvertently promote discriminatory practices if trained on biased data. Amazon, for example, had to stop using this technology in recruitment selection when it started blanket-rejecting women.

Ethical AI implementation requires transparency, fairness, and regular evaluation to ensure systems are operating as intended without unintended negative consequences.

THE FUTURE OF AI IN FM

As AI continues to evolve, the FM industry must take a proactive approach, combining human expertise with machine intelligence. By addressing data quality, contextualising AI insights, upgrading systems, prioritising customer interactions, funding responsibly, and committing to ethical standards, FM organisations can harness AI’s potential to improve efficiency without sacrificing the essential human touch.

A balanced, thoughtful approach will ensure that AI serves as a valuable partner in the FM world, enhancing—not replacing—the human workforce.

Top AI functions that can support the FM sector:

• Machine learning and predictive analysis: Interpreting data from sensors and real-time inputs
• Drone technology: Mapping sites to identify areas of repair and providing estimated costs.
• Computer vision algorithms: Analysis of visual data to determine occupancy data and security of the building.
• Generative AI: Exploring options for design.
• Energy management: Analysing historical energy to predict the optimal energy consumption.
• Decision engines: Using prescriptive analytics to make data-driven decisions.