FM, like many sectors, stands at a pivotal crossroads, with AI dangling the seductive potential to transform the way the industry operates – from the mechanics of asset protection and maintenance, to realising digital transformation and automated workflows that will materially improve the efficiency and effectiveness of teams.
Whilst I remain very comfortable with the increasing application of AI, there are legacy challenges and realities within. Understanding these barriers, and addressing them for future integration, will support a more seamless transition. The human touch must never be ignored; AI should always enhance and strengthen our customer relationships and service quality says Steve McGregor, group MD for DMA, a leading supplier of hard FM, M&E maintenance and buildings maintenance services in the UK.
The road ‘bumps’
Some operational aspects within FM are yet to align with AI due to older legacy systems, fragmented data, and workforce challenges.
• Legacy systems and infrastructure: Many FM organisations rely on outdated modular systems that were not designed for AI integration. Building management systems (BMS), for instance, often operate on closed protocols, making data extraction and real-time analysis difficult. These systems lack the interoperability required for AI to function effectively, creating silos that hinder seamless data flow.
• Data issues: AI needs live, high quality data to ensure accuracy and prevent bias. However, FM data is frequently scattered across disparate platforms, including spreadsheets, old databases, and vendor systems. This fragmentation leads to inconsistencies and gaps in information, which compromise the accuracy of AI-driven insights.
• Resistance to change: The FM sector is notoriously behind the curve when it comes to adopting new ways of doing things. Spreadsheets are clung to despite having better ways to automate processes, such as the latest workflow management software, which can, when the time is right, be enhanced by AI.
• Lack of standardisation: FM processes often lack standardisation, making it challenging for AI algorithms to generalise across various scenarios. Customising AI for specific sites, services or assets will become cost prohibitive without standardised operational processes and live accurate data inputs.
Smoothing the road
While there are incompatibilities between AI and FM mechanisms as they stand today, they are not insurmountable, and businesses can smooth the way for a more data-driven future. But you must have a very clear definition of the problems you want to solve and an equally clear vision for what ‘better’ looks like.
Standardising your business processes and automating your workflows is an important pre-requisite for service providers, because if AI is to simulate the intellectual processes of people, it needs to know how you work.
Without a clear A-to-Z line of sight and uninterrupted operational data, AI is unlikely to improve working practices, efficiency or customer satisfaction.
A few key considerations when integrating AI into your FM operations
• Don’t make mistakes when implementing facilities management apps
• Avoid unintentional waste crimes
• Get to grips with assets for proactive M&E management
• Upgrade to smart systems: Conduct an audit to identify legacy systems, data silos, and manual processes that need upgrading.
Prioritise areas where AI can deliver the highest ROI, such as business process automation in service delivery, energy management or tenant experience. Smart sensors and cloud-based platforms can provide the real-time data streams that AI needs.
• Centralise and clean data: Establish a centralised data repository and clean data by removing duplicates and standardising formats.
• Educate and reassure: Businesses should engage staff and customers to communicate how AI can enhance, rather than replace, human roles. For instance, predictive maintenance tools can identify issues before they escalate, reducing unplanned callouts, breakdown and downtime risk.
• Test AI on a small scale: Using predictive analytics for a specific asset is a good example. A tiered roll-out will build organisations’ confidence and refine their approach before scaling up.
The FM sector has much to gain from AI, but its full integration requires overcoming significant challenges. By addressing legacy systems, standardising processes, and fostering a culture of innovation, the road to AI can be navigated successfully. Even if your business is not yet using AI, laying the right foundations now could make the eventual transition less of a culture shift.