By Mike Talbot, Chief Technology Officer at SFG20
Artificial intelligence is reshaping the digital construction and facilities management landscape. From predictive analytics to automated data analysis, AI in building maintenance is increasingly positioned as a solution for improving efficiency, reducing costs and extending asset life. For duty holders, facilities managers and asset owners, the appeal is clear: smarter insights, faster decisions and data-led maintenance strategies.
However, the use of AI in facilities management is not without risk. While AI can support research, analysis and asset optimisation, over-reliance on automated systems, particularly for creating building maintenance schedules, can undermine statutory compliance and safety, especially in higher-risk buildings. Understanding where AI adds value, and where human expertise remains essential, is critical to responsible adoption across the built environment.
The benefits of using AI in building maintenance
Using AI tools for deep research
AI is highly effective at processing large volumes of information quickly. In facilities management and digital construction, this capability can support deep research into maintenance technologies, asset performance data, regulatory updates and market intelligence. AI-powered research tools can synthesise technical documentation, guidance notes and industry publications far faster than manual methods.
For facilities managers, this means quicker access to relevant insights when assessing maintenance approaches or evaluating new solutions. Importantly, AI does not replace professional decision-making in this context. Instead, it supports it by freeing up time for practitioners to interpret findings, assess risk and apply knowledge to specific operational environments.
Leveraging AI to review and challenge existing approaches
AI can also play a useful role in reviewing and challenging existing maintenance processes. By scanning contracts, asset registers or maintenance records, AI tools can identify inconsistencies, missing information or potential compliance gaps. In facilities management, this capability can prompt a reassessment of workflows, highlight areas of inefficiency and support continuous improvement.
When used appropriately, AI acts as a second layer of scrutiny, helping organisations identify issues that may otherwise be overlooked. This is particularly valuable in complex estates where large volumes of documentation and data make manual review time-consuming and resource-intensive.
Maximising asset lifespan through predictive maintenance
One of the most widely cited benefits of AI in building maintenance is predictive maintenance. By analysing performance data, usage patterns and historical faults, AI-powered systems can identify early indicators of asset failure. This allows maintenance teams to intervene before breakdowns occur, reducing disruption and unplanned costs.
Predictive maintenance can help avoid both over-maintenance and under-maintenance, optimising asset performance and extending lifecycle value. However, it is essential to note that this approach is not applicable to statutory maintenance requirements, where legal obligations dictate frequency and scope regardless of condition or performance data.
The risks of using AI in facilities management
Despite these advantages, significant risks arise when AI is used beyond its appropriate scope, particularly when it is relied upon to generate maintenance tasks and schedules.
Lack of human judgement in contracts and maintenance planning
AI-generated maintenance schedules and contract clauses may appear comprehensive, but they cannot replace the judgement of experienced engineers and facilities professionals. Competent practitioners interpret legislation, assess risk and apply standards within the context of a specific building, asset type and operational environment.
AI systems tend to treat guidance as static, failing to recognise nuance. They may reflect outdated legislation, incomplete standards or superseded Approved Codes of Practice, creating a misleading impression of compliance. An experienced professional, by contrast, understands when guidance has changed, when manufacturer recommendations should be challenged, or when building-specific risks require a more conservative approach.
Human judgement is also essential for understanding how assets behave in real-world conditions. Changes in occupancy, usage patterns or environmental factors can significantly alter maintenance requirements. While AI may generate a schedule based on assumed usage, only a qualified professional can assess whether that schedule remains appropriate and compliant.
Inability to adapt to unforeseen circumstances
AI systems excel at identifying patterns, which makes them effective for predictive analysis. However, this strength can also be a limitation. Unexpected events—such as changes in building use, emergency situations or sudden increases in demand—may require immediate adjustments to maintenance regimes.
AI-generated schedules may not respond quickly or appropriately to these changes, potentially resulting in delayed or inadequate maintenance. In high-risk environments, this lack of adaptability can have serious safety and operational consequences.
The risk of outdated or incomplete regulatory content
A critical concern in AI-driven building maintenance is the risk of relying on outdated content. Maintenance obligations in the built environment are not static. Legislation, regulations and industry standards evolve over time, and maintenance strategies must evolve with them.
If an AI system is trained on outdated sources or fails to incorporate the latest regulatory updates, it may generate schedules that omit new requirements or reference superseded standards. This can expose organisations to enforcement action, contractual disputes, insurance challenges and increased liability, particularly in sectors such as healthcare, residential and public buildings.
Beyond immediate accuracy, there is also the issue of long-term defensibility. Duty holders must be able to demonstrate that their maintenance strategies have remained compliant as the law has changed. AI-generated schedules that are not explicitly grounded in current legislation make this increasingly difficult.
Valuable role
AI has a valuable role to play in digital construction and facilities management. Used responsibly, it can support research, enhance review processes and contribute to more informed asset management decisions. Predictive analytics, in particular, offer clear benefits when applied within appropriate boundaries.
However, AI should not be treated as a substitute for professional judgement, especially when it comes to statutory compliance and building maintenance schedules. The risks associated with outdated information, lack of contextual understanding and limited adaptability are significant, particularly in higher-risk buildings.
For organisations seeking to adopt AI in building maintenance, the most effective approach is a balanced one. AI should support, not replace, experienced facilities professionals. By combining technological capability with human expertise, the sector can harness the benefits of AI while maintaining safe, compliant and defensible maintenance strategies across the built environment.
Read next: BIM as an Enabler of Circularity in Construction – Build in Digital
Are you a building professional? Sign up for a FREE MEMBERSHIP to upload news stories, post job vacancies, and connect with colleagues on our secure social feed.
