Brad Haeberle, executive vice president, service, Siemens Smart Infrastructure Buildings, looks at the role of AI in operations.
Digitalization, climate change, the shortage of skilled maintenance professionals, compliance reporting, cost pressures, and basic hot and cold calls—these are just a few of the daily challenges facility managers are up against.
As the list of responsibilities grows, so does the pressure. Will Artificial Intelligence (AI) relieve some of the burden, or simply become another layer of complexity?
Around the world, we’re seeing real-life examples of how AI and emerging technologies are already helping facility professionals tackle these challenges. The transition to digitally enhanced building operations is not only underway—it’s essential. AI is no longer a future consideration; it's a critical tool in the move from smart to autonomous buildings.
Pressures facility managers face today
Facility managers are facing mounting pressure from all sides. Digital transformation is accelerating, yet many buildings still rely on legacy systems that are difficult to integrate.
At the same time, energy costs are rising, and ambitious sustainability goals require new approaches to efficiency. Staffing shortages only add to the challenge, with fewer skilled technicians available to maintain increasingly complex systems.
Compliance and documentation requirements are becoming more demanding, while expectations for safety, security, and occupant comfort continue to grow.
And through it all, budgets remain tight. Meeting these demands requires more than traditional tools. Facility leaders need intelligent, scalable solutions—and AI is emerging as a powerful ally to help navigate this new reality.
The role of AI in facility management
The rise of AI has already transformed countless industries and buildings are no exception. From optimizing energy usage to automating security alerts, AI is redefining what efficient, resilient building management looks like.
In effect, AI is giving buildings a “digital nervous system,” empowering them to identify inefficiencies, initiate resolution workflows, and keep critical systems—such as HVAC, access control, and fire alarm systems—running optimally without human oversight.
Yet this shift isn’t about replacing human expertise. It’s about enabling people to make better decisions, faster - guided by real-time insights and predictive intelligence.
Buildings today generate more operational data than ever before. But raw data is not insight. AI helps filter, analyze, and connect that data to decisions—turning overload into action.
As building operations evolve, service models are also transforming—from task-based to outcome-driven. AI enables this shift by providing transparency, KPIs, and actionable insights to measure what really matters: performance, efficiency, and occupant comfort.
Global use cases: AI solving real problems
Sustainability & energy efficiency
Energy consumption remains one of the largest operational costs and a primary driver of emissions in commercial buildings. AI is helping facility leaders turn energy challenges into sustainability wins.
By continuously monitoring usage patterns and forecasting energy demand, AI systems dynamically adjust building operations—modulating HVAC, lighting, and shading systems to align with occupancy, time of day, and weather conditions.
These intelligent systems can also integrate on-site renewables, battery storage, and utility demand response programs. The outcome: reduced emissions, lower energy bills, and verifiable progress toward ESG goals.
A practical example is the automation of energy anomaly detection. Traditionally, creating consumption baselines and identifying irregularities was a manual, time-consuming, and error-prone process that often diverted attention from more strategic tasks. Now, AI steps in with a self-learning system that automatically generates daily energy consumption patterns based on the previous day’s data. This enables continuous, adaptive monitoring and allows unusual consumption behaviors to be detected immediately. Facility managers are promptly notified of deviations, enabling swift corrective action—without the need for constant manual oversight. The result is a smarter, more responsive building operation that continuously optimizes itself in the background.
Physical security
Security teams face a flood of data, alerts, and alarms—many of which are false positives. In access control systems, incorrect configuration, aging hardware, or misuse frequently trigger false alarms that distract operating personnel and generate unnecessary costs for alarm verification. AI helps address this challenge by identifying false alarms and diagnosing their root causes. Through automated recommendations for mitigation, these systems reduce the number of false positives and shift the focus back to real security incidents.
The result: a significant reduction in false alarms, improved operational efficiency, and lower verification costs—enabling security teams to respond faster, more accurately, and with fewer disruptions.
Workflow automation & field operations
With ongoing labor shortages, facility teams are under pressure to do more with fewer resources. AI steps in to help prioritize and streamline field operations. Using real-time data and generative AI, service requests and technician schedules are optimized based on job urgency, location, and availability. The system ensures the right person is dispatched at the right time—reducing delays and improving first-time fix rates. In addition, machine learning models perform automated root cause analysis, enabling the system to identify and address underlying issues rather than just symptoms.
Beyond reactive fixes, predictive and prescriptive AI services analyze critical building systems continuously—anticipating issues before they occur and prioritizing actions based on impact and cost savings. This automation extends to generating and managing workflows, including automatically raising service tickets with all relevant information pre-filled, thereby maximizing efficiency for onsite technicians and service partners. This proactive, coordinated approach boosts operational efficiency and enhances satisfaction among both staff and building occupants.
How to start the AI journey
Getting started with AI in building operations doesn’t require a major overhaul—it starts with a digital readiness check: Are systems connected? Is data flowing freely? Where are the operational bottlenecks?
From there, start small. Focus on high-impact, low-effort use cases like predictive maintenance or smarter alarm handling. These quick wins build confidence and demonstrate value early.
Next, modernize infrastructure to enable seamless data integration and visibility across systems. Set clear KPIs and ROI targets to measure progress and guide scale-up efforts.
Just as important: empower your teams. Help staff understand AI as a support tool, not a replacement—enhancing their expertise with better insights and decision-making power.
With a clear, phased approach, facility leaders can make AI adoption practical, measurable, and aligned with long-term operational goals.
Conclusion
AI is no longer just hype—it’s already addressing real challenges in building operations. From reducing false alarms to optimizing energy use and scheduling, the benefits are both tangible and measurable.
Autonomous buildings won’t emerge overnight. But with AI laying the groundwork today, facility teams can take strategic, deliberate steps toward more resilient, efficient, and user-centric operations—without losing sight of the human expertise that remains vital to long-term success.
Now is the time to start small, think big, and build smart: identify key pain points, explore AI-powered solutions that deliver quick wins, and scale what works.
The journey has begun - and with the right mix of intelligence and experience, facility leaders can shape a smarter, more adaptive future, one step at a time.