The role of AI in facilities management: an overview

With the advent of Internet of Things (IoT) sensors and the increasing availability of real-time data, AI is playing an increasingly important role in FM.

IoT sensors allow facilities teams to maintain a comprehensive view of their assets, occupancy and usage levels. Deployed at scale, however, IoT sensors can generate millions of data points, and collating and making sense of this level of information can be extremely challenging.

AI can analyse huge data sets much faster than any human, and spot trends which might not be obvious to derive powerful insights. By cross-referencing sensor data with business insights or even environmental data such as weather patterns, it can help to predict usage and cost levels, spot inefficiencies and identify new ways to enhance user experiences or reduce expenses.

Moving from reactive to proactive maintenance

AI is also helping facilities managers move from reactive to proactive maintenance by providing insights into when maintenance is needed and what needs to be done. By analysing data from IoT sensors, AI algorithms can identify when maintenance is required, minimizing downtime and reducing costs.

For example, bathroom facilities might use footfall tracking to schedule maintenance visits after a certain number of uses, or sensors on soap or paper dispensers might trigger an alert when their capacity reaches a specific level, prompting teams to refill them. This information can be used to schedule maintenance at the right time, avoiding unnecessary visits and reducing costs whilst ensuring that a high standard of cleanliness is maintained at all times.

Predicting and preventing problems in real time

By analysing historical data from IoT sensors, AI algorithms can identify patterns and trends that indicate potential issues. For example, if an HVAC system consistently reports a higher than average internal temperature, it may be a sign that maintenance is needed. Using this information, facilities managers can schedule maintenance before theW system fails, preventing downtime and minimizing disruptions to business operations.

AI-powered predictive analytics tools can not only identify potential problems in real time, they can trigger alerts and tasks in CAFM systems, flagging issues with the right team members and allowing facilities managers to take action quickly.

Reducing energy usage and meeting ESG targets

AI is playing an important role in reducing energy usage and meeting environmental, social, and governance (ESG) targets by providing insights into building performance and identifying opportunities for improvement. By analysing data from IoT sensors, AI algorithms can identify areas where energy consumption is high and recommend ways to reduce it.

For example, if an HVAC system is running when the building is unoccupied, AI algorithms can automatically turn this off to reduce energy usage when no one is in the building. This information can be used to reduce energy costs and improve overall sustainability performance.

AI-powered predictive analytics tools can also optimise wider building performance. For example, flexible working patterns could be analysed to understand whether it’s necessary to keep all parts of a building open at all times, or whether it could be more efficient to close down floors when occupancy is low, reducing the need to for heating and lighting across the entirety of the building.  This information can be used to develop and implement strategies to reduce energy usage and achieve ESG goals.

Delivering better occupier experiences

AI-powered systems can help to provide enhanced experiences to occupiers, improving satisfaction. For example, AI-powered scheduling could automatically assign the most appropriate spaces to users booking facilities, as well as offering relevant additional services where appropriate. AI chatbots could support with customer service, smoothing the process of reporting maintenance issues by ensuring the right information is collected first time.

AI can also ensure that buildings adapt to their occupiers’ usage patterns. For example, if a site is regularly used outside of normal office hours, AI could detect this trend and automatically schedule HVAC and lighting to activate at the right time, providing a more welcoming environment for occupiers when they arrive.

Driving efficiencies and lowering operational costs

AI is also helping facilities managers drive efficiencies and lower operational costs by providing insights into how buildings are being used and identifying areas for improvement. By analysing data from IoT sensors, AI algorithms can identify patterns in building usage, such as which areas are most popular or where occupants tend to spend more time. This information can be used to optimize building layouts and design, as well as to allocate resources more effectively.

AI can also be used to maximise the efficiency and effectiveness of maintenance teams. By accurately triaging maintenance requests, AI-driven automations can ensure that the right teams are dispatched with the correct parts and equipment, to maximise the likelihood of issues being fixed first time. For maintenance teams working across multiple sites, AI can boost efficiency by effectively scheduling tasks to minimise travel time, maximising productivity and reducing mileage and travel costs.

Start your shift to AI-powered facilities management

AI is playing an increasingly important role in facilities management by providing insights into building performance, identifying potential issues before they occur, optimizing resource allocation, and reducing operational costs.

To find out more, download our [ebook], The role of AI in facilities management.