Artificial intelligence (AI) is rapidly securing a foothold in the facility management space. A quick Google search for “AI tools for facility management” will produce a host of companies offering AI-driven tools to help with everything from maintenance management to space optimization.
Facility managers who are eager to exploit the benefits of AI-driven tools should proceed with caution because AI, like any emerging technology, has its own pros and cons. To minimize risks while maximizing impact, facility management professionals should carefully consider the following factors.
Boosting Profitability Requires an Investment
There are many ways that AI-driven tools can boost profitability in facility management. In most cases, these tools leverage data from facility systems to enhance performance.
For example, AI-driven HVAC systems assess data and develop operational protocols that increase efficiency, including the tracking of occupancy patterns inside of facilities and weather patterns outside of facilities. Sophisticated systems will even consider building orientation and the surrounding landscape in a way that allows for fine-tuning of HVAC performance.
The same benefits can be achieved with lighting systems that leverage AI and machine learning. These systems can reduce light at times when the work environment is supplemented by natural lighting and turn off lights in spaces that are unoccupied.
Every facility manager knows the frustration associated with lighting and cooling expenses created by spaces that are unoccupied. Some statistics show as much as 20% of energy costs in commercial buildings go to support lighting, and studies on HVAC have shown it accounts for as much as 40% of overall energy expenses. Integrating AI with HVAC and lighting systems creates opportunities for greater efficiency through detecting and addressing waste, often in an automated way.
Preventative maintenance is another area in which AI can be leveraged to improve facility management. Unexpected breakdowns often require emergency repairs, which means increased costs for facility management, as well as frustration for facility users. AI tools can use data on equipment performance to determine the most efficient maintenance schedule.
When combined with sensors that report real-time performance metrics, AI can also be used to predict when equipment is likely to fail. This involves identifying deviations from normal operating conditions, such as changes in energy consumption or operating temperatures. Using AI in this manner can empower predictive maintenance that allows facilities to avoid the costs associated with equipment downtime.
The downside to leveraging these AI-driven efficiencies is that they require a significant investment on the front end, as new tools must be obtained and integrated into existing systems. This involves making investments in hardware, software, and training.
The hardware needed to power AI-driven systems starts with the devices that are used to collect data, including sensors that detect occupancy, temperature, and light levels. Once data is collected and analyzed, hardware is needed to control systems in a way that delivers AI-inspired optimizations.
Software for analyzing data is another investment that must be considered. Often, this is not a one-time expense. Software is typically licensed, which means the expenses associated with it are ongoing.
Organizations also must consider the costs of storing data. Tracking and analyzing facility usage in order to identify trends and optimize systems is an ongoing process that requires a constant flow of data. If data is not up-to-date and accessible, the results provided by AI will not be reliable.
Finally, organizations must also consider the investment that is needed for educating those who will interact with AI-driven systems. For those who manage facilities, this involves training staff on how to oversee new systems and the expected impacts.
Facility managers should also help those who occupy facilities understand how AI-driven systems will affect their experience. Recent reports about the dangers of AI have led many to become wary of its use. As AI systems are rolled out, those who will interact with them should understand their capabilities and limitations.
Collecting Data Also Requires Safeguarding Data
AI runs on data, meaning the better the data it is fed and uses, the better the output will be. The ongoing collection of data, however, requires that organizations have a plan for data management that addresses relevant concerns.
As AI has been embraced in the business world, some of the biggest concerns expressed by experts have centered on how data is managed. To protect privacy and avoid the unethical use of data, organizations have been challenged to develop highly secure systems that protect the privacy of the data that they collect and prevent cases of unauthorized use.
Facility security provides one example of an area in which AI-driven tools increase value, but also risk. AI-enhanced security can help to identify concerns as they are happening, such as detecting the presence of a gun on a person who has entered a facility. AI can also help to search through archived surveillance footage to identify circumstances that are later found to be important, such as a person wearing a particular outfit or driving a particular car.
While the data that empowers these types of security enhancements can be life-saving, it also creates the potential for abuse. Video footage can be misused in ways that involve an invasion of personal privacy and can be used for profiling or discrimination, which can be considered a violation of civil liberties.
These abuses represent just some of the ethical concerns that have been raised about the unauthorized use of data collected to fuel AI. To ensure that safeguards are in place, facilities must establish clear guidelines for AI integration before they begin using it. These guidelines should stipulate how data will be collected, stored, and accessed.
There are a number of significant advantages that businesses can gain from integrating AI into strategies for facility management. However, if proper precautions are not taken, the pros of using AI can quickly be overshadowed by the cons. Facility managers must make sure they implement new capabilities in a way that mitigates risks and supports their overall management strategy.
Bryan Kelley is the co-founder and CEO of full-service provider Laser Facility Management and holds decades of experience in project management as a licensed general contractor.