From SFG20

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. 

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. 

Andi Connelly Horsley, Technical Content Manager at SFG20 said:

“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. 

Chris Adams, Chartered Engineer and Director of IoFMT Professional Services Limited said:

“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. 

 Darien Jay, CEO of Vixus Property Advisory, said:

““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. 

From SFG20, an exhibitor at Facilities & Estates Management Live.

The NHS estate has long faced a serious and growing challenge: an overwhelming £13.8 billion backlog in essential maintenance, with costs only rising. Delays in upkeep not only endanger patient safety but can also expose Trusts to legal risks, including fines and increased long-term expenditure.

33% of building maintenance professionals reported “defending maintenance budget cuts” as their biggest challenge*, a problem intensified by the Building Costs Information Service’s prediction of a 4.8% rise in maintenance costs in 2023.

In response, Paul Bullard, Product Director at SFG20, the industry standard for building maintenance specification, has shared a step-by-step framework to help address the £13.8 billion maintenance backlog, even amid tight financial constraints.

Reflecting on the true costs of inaction and the risks posed by failing assets, the following strategies identify proven methods for healthcare estates to manage budgets better during inflationary pressures. 

1. Establish risk appetite and tolerance

To begin addressing the NHS maintenance backlog, organisations must first define their risk tolerance and appetite, the level of risk they are willing to accept to meet strategic objectives. 

Clearly articulating this helps inform cost forecasting and ensures consistency across decision-making and governance. A well-defined risk appetite supports better prioritisation, reduces uncertainty, and strengthens spending reviews and resource allocation.

2.                  Fix your asset register

Accurate and up-to-date asset registers are critical for maintenance planning, compliance, and safety in NHS estates. They are also a fundamental part of the Golden Thread of Information under the Building Safety Act 2022, supporting transparency and accountability throughout a building’s lifecycle. 

Despite this, 43% of organisations report poor data accuracy, and 6% have no register at all**. 

After creating or fixing your asset register, the next step is to match your assets within your asset register to the right maintenance tasks.

3.                  Understand your statutory obligations

Delays in maintenance, especially those that are critical, can result in ward closures, cancelled treatments, and increased costs across NHS estates. While non-statutory tasks fall outside legal requirements, completing them can often play a key role in preventing asset failure and minimising disruption. 

The Government’s FMS 002: Asset Data standard emphasises the use of SFG20 criticality codes as a basis for producing complete and accurate asset registers. Aligning with this guidance helps healthcare estates plan effectively, manage risk, and maintain safe, compliant operations.

4.                 Cost forecasting

Effective maintenance planning depends on applying compliant, standardised tasks to each asset and accurately forecasting the associated costs. Facilities management technologies, such as CAFM systems with integrated finance modules, can support this by linking asset data with cost and compliance tracking.

Without this structure, NHS trusts may struggle to communicate risk profiles and budget needs to decision-makers, hindering efforts to reduce the growing maintenance backlog and increasing exposure to serious legal, financial, and reputational consequences.

When SFG20 spoke to David Hemming, Civil Engineer and leading FM expert at NHS Shared Business Services, he said:

“Currently, the NHS uses the Premises Assurance Model when they [the board of each trust] look at assurance… they could benefit from having a more directed tool to really understand their resources and their finances, to say this is what we need to get on top of it.

“This is important because if you’re doing asset management well and you’ve integrated tools like SFG20 into CAFM systems, asset management systems, enterprise asset management systems etc., then you should have a clear horizon of when you need to undertake tasks, what it’s likely to cost and the risks involved by not doing it. 

“This is important because it gives you a rich risk picture that you can then use to brief the decision makers about finances and resources.

“Doing things in a standardised way is invaluable and therefore doing a procurement/investment strategy that is linked to that, can save you thousands and thousands of pounds.”

According to a recent survey, by SFG20, the industry standard for building maintenance, 34 per cent of facility maintenance professionals do not update their asset registers or do not know how frequently they are updated. Only nine per cent believed their asset registers to be 100 per cent accurate and up to date, with a further 37 per cent stating their register is at most 50 per cent accurate. 

SFG20 surveyed 190 professionals from various sectors to assess challenges and priorities regarding facility management for its State of FM Report 2025. The survey reveals that asset registers were the leading investment priority for respondents over the next three years, spotlighting the industry-wide issue that FM professionals face in keeping their registers complete and updated. 

The report also reveals that almost a third of FM professionals (31 per cent) still keep their asset registers in a spreadsheet. A further five per cent have a mix of software, spreadsheets, and paper-based registers, splitting their assets across different formats. 

Davy Clark, Implementation Consultant at SFG20, said: “One of the most common issues we encounter is the lack of consistency and specificity in asset registers. Too often, assets are recorded with vague descriptions like ‘boiler’ or ‘pump,’ making it incredibly difficult to map them to the correct maintenance tasks. 

“Several factors contribute to this challenge, including the collection of asset data across large estates, which may have been surveyed at different points in time and by different people, causing inconsistencies in data quality and accuracy. 

“This leads to inefficiencies, increased risk, and compliance challenges. Ensuring asset data is consistently structured, complete, and digitally maintained in a single source of truth is essential—not only for effective planned maintenance but also for long-term cost savings and compliance.”

Words by Mike Talbot, CTO at SFG20, the industry standard for building maintenance

Artificial Intelligence 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. 

AI in the building maintenance industry leverages machine learning algorithms and data analytics to enhance efficiency, cost-effectiveness, and overall performance of building maintenance processes. Used for predictive maintenance, energy management, and smart building management systems, AI technologies come with a host of benefits. 

Recent technologies can summarise maintenance schedules for quick reference, highlighting asset types and locations, easing the process for engineers and facility managers. Similarly, AI is capable of analysing asset register data to automatically identify and map appropriate maintenance schedules to each asset – a task that frequently takes months to do manually. 

What are the pros of using AI technologies in a building maintenance strategy? 

1. Cost reduction 

AI can automate the repetitive tasks associated with setting up maintenance plans and ensuring they are optimal and legally compliant. Efficient and effective maintenance relies on a strong understanding of the facilities and assets that require maintenance and an informed plan to address them. AI provides a new capacity to create a deeper understanding that would be unfeasibly costly to implement using human resources.

AI can be used to minimise maintenance costs by decreasing unplanned downtime and optimising energy consumption. 

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. 

2.  Time-efficiency 

By automating tasks, AI tools can help maintenance professionals work more efficiently by streamlining processes and cutting down on timely repetition. AI software tools can assist with many traditionally manual tasks, speeding up repetitive processes and helping to standardise data. In the long term, this can save those responsible for building maintenance both time and effort, which can be used in more strategic, high-impact areas.

3.  Maximises asset lifespan 

AI-powered solutions can extend asset lifecycles by predicting potential failures before they occur. By recommending the best timing for maintenance (not applicable for statutory requirements), AI can, in turn, prevent both over-maintenance, which can cause unnecessary wear, and under-maintenance, which can lead to premature failure.

4.  Provides more reliable reporting and analytics 

AI in facilities management is incredibly helpful for collecting, analysing, and simplifying the array of information involved with building maintenance and its associated responsibilities, including diagnosing problems. 

Machine-learning AI can 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 example, previous patterns of equipment failure.  

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. 

What are the cons of leveraging these technologies?

1. 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, such as sensor installation and integrating AI solutions. This upgrade can be particularly costly for older buildings. 

Implementing AI systems can require significant upfront investment in hardware, software, and training, so careful planning and budgeting are essential for a successful and cost-effective onboarding.

2.  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 an organisation.  

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 this data is collected, stored, and used in compliance with privacy regulations is crucial. 

3.  Overreliance 

Industry professionals must always approach AI adoption with caution and not fall into a cycle of overreliance. Artificial intelligence tools are not infallible; they require rigorous data validation and continuous human oversight. Facility management systems are complex and demand nuanced interpretation that AI algorithms may not fully comprehend

According to a recent survey, improving compliance and safety continues to be the number one priority for facilities management professionals. However, 14% of respondents expressed uncertainty about meeting building maintenance compliance standards, while only 23% plan to increase their investment in compliance and safety measures.

SFG20, the industry standard for building maintenance, surveyed 190 professionals from various roles in the built environment sector to assess challenges and priorities regarding facility management. The survey reveals that while the industry faces significant pressure, professionals are focused on innovation and improvement, with clear priorities and strategies for 2025.

Compliance and safety as top priority

The survey reveals that improving compliance and safety remains the top priority for facilities management professionals. A significant 77% of respondents reported compliance to be at least a moderate challenge, reflecting the ongoing issue of meeting complex regulatory requirements. 

Budget constraints and cost reduction

Budget constraints are currently the biggest challenge in the industry, as reported by 75% of respondents. At the same time, reducing operational costs is the second biggest priority for FM professionals. Rising energy costs, inflation, and supply chain disruptions all make it increasingly difficult to deliver quality and cost-efficient services within tight budgets.

As organisations strive to meet compliance demands and implement essential safety measures, 40% report a budget decrease over the past year, with 13% citing a significant reduction. 69% of facilities management professionals have the same or less budget than the previous year.

Meanwhile, staffing shortages are widening the talent gap in facilities management, with 80% of professionals reporting their facility management teams are understaffed, and 24% stating they are significantly understaffed.

Technology adoption 

Digital transformation has become a core focus within the FM industry, as organisations seek to lever technology to improve efficiency, reduce operational costs, and enhance compliance. 53% of respondents rated digital transformation as a ‘highly important’ strategic priority for their organisation. 

However, high costs remain a major obstacle to technology adoption in facilities management, with 33% stating it as their main barrier. Many facility management teams work under tight budget constraints, making large-scale investment in digital advancements a struggle. Other challenges revealed were: integration with existing systems (19%), a lack of internal expertise (16%), and a resistance to change within the organisation (17%).

Kirsty Cogan, Managing Director at SFG20, says:

“As the facilities management industry evolves, improving the quality of asset data, achieving compliance, and controlling costs will be the key priorities in 2025. The survey findings highlight the significant pressures faced by professionals in the sector but also show how they are driving change and innovation to address these challenges.

“It’s encouraging to see the industry increasingly prioritising technology as a vital tool for achieving compliance and reducing operating costs. To overcome the significant challenges facing the sector, technology must play a central role. Recognising this, SFG20 are incorporating technologies such as AI search and asset mapping into our software and developing API integrations to assist industry with FM systems connectivity. A great way to start is to build a technology roadmap that is aligned to your organisation’s objectives”