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AI In The Building Maintenance Industry: Pros, Cons, Examples & Trends
Table of Contents
- What Is Artificial Intelligence (AI) In The Building Maintenance Industry?
- Examples Of AI In The Building Maintenance Industry
- What Are The Pros Of Using AI In The Building Maintenance Industry?
- What Are The Cons Of Using AI In The Building Maintenance Industry?
- Emerging AI Trends In the Building Maintenance Industry
Artificial Intelligence (AI) is no longer a buzzword or a futuristic concept. Across many sectors, AI is being adopted in various ways, with the building maintenance industry closely following behind.
At SFG20, we’ve been the industry standard for building maintenance specification since 1990. It’s our mission to uphold building safety standards – and part of that mission is to help keep you up to speed with the latest tech developments such as AI.
We’ve collaborated with Darien Jay, CEO of Vixus Property Advisory, Chris Adams, Chartered Engineer and Director of IoFMT Professional Services Limited and Andi Connelly Horsley, SFG20’s Technical Content Manager, to bring you this article which covers all angles of AI in the built sector.
What Is Artificial Intelligence (AI) In The Building Maintenance Industry?
AI in the building maintenance industry leverages machine learning algorithms and data analytics to enhance the efficiency, cost-effectiveness, and overall performance of building maintenance processes.
AI can be used as a tool to help bring together, organise and make sense of the vast array of information involved with managing maintenance and the associated responsibilities.
However, it’s important to note that if you don’t have someone with the know-how to properly understand the implications of the data and what it affects, this is where AI can go wrong.
“To use a filing cabinet as an analogy, AI can dive in, collect and transform its contents into outputs using language models and analytics.
It can be expanded to include thousands of filing cabinets, but what it cannot do is collect the pieces of paper that sit outside the filing cabinet (that should be filed but are not for whatever reason).
AI has no reach into our physical world and as such is limited to its own boundaries. And so, for the built environment, it is about data.
It’s about how we approach the collection and standardisation of data throughout a building’s lifecycle to support the value chain from operators to suppliers and managers to investors, who are all needed to make data-driven decisions. These filing cabinets need to be sorted."
Examples Of AI In The Building Maintenance Industry
Predictive Maintenance
When used in buildings that are designed and built to minimise energy use and maintenance, AI-assisted sensor technology can bring efficiencies to a building maintenance regime.
Rather than simply raising an alert when the equipment is about to fail, AI can analyse patterns and anomalies in the data that flows through it based on set parameters, in turn providing predictions as to the timing and significance of future failures.
By analysing historical and real-time data as well as the requirements and parameters to be met, AI can be a great tool for predictive maintenance, helping to greatly inform maintenance decisions, optimise resource allocation, prevent plant failure and reduce downtime costs.
Energy Management
Although good design, thermostats, valves, sensors, controls and good building energy management systems have been able to control set parameters of buildings for decades, the use of AI can analyse far more interdependent and important data, such as occupancy levels.
AI systems can adjust the temperature in different parts of a building based on occupancy levels and external weather conditions.
By analysing data from various sources such as weather forecasts, occupancy patterns and energy usage, AI can efficiently optimise a building’s heating and cooling.
These adjustments not only reduce energy consumption but also enhance the comfort of building occupants.
Digital Twins technology, which provides a virtual replica of a physical building or environment, can gather real-time data from sensors and systems to create a continuously updated digital representation.
By monitoring, understanding and managing data, this can have a high impact on decarbonisation, energy savings and operational costs.
Smart Building Management Systems
While smart building management systems have been around for a long time, AI has now made it possible to look at historical and current data, as well as include and analyse other factors that have an impact, such as occupancy levels.
These systems use data from Internet of Things (IoT) devices to monitor and control building operations in real time.
For instance, AI can manage security systems, fire alarms and access controls to ensure that the building is safe and secure.
In light of the flexible working revolution that we have witnessed in recent years, smart building management systems are now being used to optimise space utilisation by analysing occupancy patterns.
This is particularly useful in commercial buildings, where efficient use of space can lead to significant cost savings.
By integrating various building functions, AI can help to create a more responsive and adaptive environment.
What Are The Pros Of Using AI In The Building Maintenance Industry?
Saves Money
AI can be used to minimise maintenance costs by decreasing unplanned downtime and optimising energy consumption.
Plus, as AI provides real-time data analysis and insights that can help facility managers make more informed operational decisions, this can reduce the likelihood of costly errors in judgment.
Frees Up Time
We all want to work smarter, not harder, and AI can help you to do exactly that, for example by automating repetitive tasks.
AI software tools can assist with and/or automate many traditionally manual tasks, speeding up repetitive processes and helping to standardise data.
In the long term, this can save you and your team both time and effort which can be used in more strategic, high-impact areas.
Maximises Asset Lifespan
AI-powered solutions can extend asset lifecycles by predicting potential failures before they occur.
AI can also recommend the best timing for maintenance (not applicable for statutory requirements) which in turn can prevent both over-maintenance (which can cause unnecessary wear) and under-maintenance (which can lead to premature failure).
More Reliable Reporting & Analytics
AI in facilities management is an incredibly helpful tool for collecting, analysing and simplifying the vast array of information involved with managing maintenance and the associated responsibilities including diagnosing problems.
In the past, data had to be sorted manually, with decisions often being made without clear, evidence-backed reasoning.
Now, through machine-learning AI, data reporting and analytics can be achieved faster and more reliably than ever before, lowering the risk of human error.
Machine-learning AI is able to interpret data from various sources including sensors and real-time user inputs to identify patterns and make intelligent, personalised predictions about building management needs, for e.g. previous patterns of equipment failure.
As this type of AI continuously learns and adapts, this means that its accuracy will only improve over time.
However, it’s important to remember that AI won’t always be correct, and that overreliance on it can become a problem if you’re not careful.
Although we know AI can be used for predictive maintenance in many industries, the facilities management industry may not be as straightforward: think the age-old rubbish-in-rubbish-out scenario.
“If the parameters we set for the analysis are not specific to the site or use of it, we're going to get rubbish out.
Also, having been a building services engineer for many years, I'm convinced that buildings would work perfectly well if it weren't for the fact that variables such as people, all with different requirements, are introduced to the mix!
How a building is used compared to the original intended use (and therefore design) is one of the main variables, which is why facilities management and maintenance can be so complicated.
I think you still need a good understanding of the plant, equipment, systems and building you're responsible for to ensure the information you receive isn't erroneous. But are we loading too much onto the responsible person, having to learn another mechanism for managing maintenance?
AI will be a brilliant tool for bringing together complicated data, analysing it, presenting it in a more manageable and easily understood format and diagnosing problems and potential fixes, as long as non-maintenance-related variables are included in the analysis.
Providing that AI is used as an aid and not instead of knowledge, it's intuitive to use and we give it the correct information to learn from, AI will help the industry immensely.”
What Are The Cons Of Using AI In The Building Maintenance Industry?
High Initial Costs
Despite its benefits, the implementation of AI in building maintenance is not without challenges – the most obvious being the initial cost of deploying AI systems. 
Installing sensors, upgrading infrastructure and integrating AI solutions can be expensive, particularly for older buildings.
Implementing AI systems can require significant upfront investment in hardware, software and training, so careful planning and budgeting is essential for a successful and cost-effective onboarding.
Data Privacy and Security Concerns
As AI systems collect and process large amounts of sensitive building and occupant data, this may cause privacy and cybersecurity concerns for your organisation.
Plus, as AI systems require high-quality, consistent data to function effectively, poor or incomplete data can lead to inaccurate insights or decisions.
In other words, AI is only as good as the data that goes into it.
Ensuring that this data is collected, stored, and used in compliance with privacy regulations is crucial.
Ethical Considerations
The use of AI in monitoring building occupancy and usage patterns may raise ethical questions about privacy and consent within your organisation.
Moreover, it’s important to consider the fact that certain facility management AI software tools may lead to role changes or even job losses in some areas of your organisation.
"By understanding the problem to be solved and how it will bring value, as well as applying engineering principles with data standardisation combined with development pathways of competency, the risk of adopting AI can be suitably and sufficiently managed."
Emerging AI Trends In the Building Maintenance Industry
We are now starting to get a glimpse of emerging AI trends set to shape the industry, and depending on your stance, this will either excite or terrify you.
One such trend is the increasing use of AI-powered robots for process-type installations.
These robots can perform routine inspections, clean surfaces and even carry out repairs, reducing the need for human intervention.
WARNING: Some tasks are required to be carried out at a set frequency, as dictated by legislation or supporting guidance, and cannot be negated by the use of AI. Some tasks require a visual inspection or interaction, and others rely on the experience and competency of the engineer to evaluate the installation in person.
Another trend is the integration of AI with other advanced technologies such as Augmented Reality (AR) and Virtual Reality (VR).
These technologies can provide maintenance teams with real-time information and visualisations, enhancing their ability to diagnose and address issues.
Moreover, as AI technology continues to evolve, we can expect more sophisticated predictive maintenance algorithms that can analyse even larger datasets and provide more accurate predictions.
“For those who still fear the rise of machines, AI is not about replacing humans.
History shows that the human workforce is remarkably adaptable.
No doubt some may see the dawn of AI as their time to take early retirement, but the next generation of recruits will invariably be more tech-savvy.
They will be the engineers who design and operate AI so that it delivers optimal efficiency for buildings.
Those who adopt AI early and wholeheartedly will be at the forefront of the building maintenance revolution.
The question you need to ask yourself is: are you going to be there with them?”
The Future Of Facility Management (FM) Software
The way that we are communicating and capturing information is changing, and there’s no denying the fact that AI has brought about a paradigm shift in the building maintenance industry.
In most cases, rather than fully replacing roles, AI can act as a supplementary tool to reduce manual, repetitive tasks, better understand assets, save time, conserve resources and reduce costs.
At SFG20, our long-term mission is to make buildings as safe as they can be. If you’re keen to learn more about future FM software trends and how to make your building smarter, safer and more sustainable, take a read of our ultimate guide below.
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