Reducing energy costs through smart building automation, sensor technology and AI

Energy is one of the largest controllable costs in facilities management, and with rising prices, tightening budgets, and ambitious Net Zero targets, the pressure to reduce consumption has never been higher.

Advances in smart building automation, sensor technology, and AI-powered analytics are transforming the way facilities managers monitor, control, and optimise energy usage. Instead of relying on fixed schedules or manual interventions, FM teams can now make dynamic, data-led adjustments that significantly reduce costs while maintaining comfort and operational efficiency.

Why traditional energy management falls short

Historically, energy-saving efforts have been hindered by two big challenges:

1. Lack of real-time visibility: Without accurate, up-to-the-minute data on energy consumption and environmental conditions, it’s difficult to pinpoint inefficiencies.
2. Reactive approaches: Adjustments are often made after the fact, once high bills or operational issues highlight a problem.

These methods not only miss opportunities for savings but also risk inconsistent results. Energy performance can fluctuate wildly depending on weather, occupancy patterns, and asset health, which traditional systems struggle to account for in real time.

Smart building automation: The first layer of savings

Modern building automation systems (BAS) integrate directly with HVAC, lighting, and other critical systems, allowing FMs to fine-tune performance based on live data.

For example:

• Automated HVAC control can adjust temperature and ventilation based on occupancy, external weather conditions, or even the number of people in a room.
• Intelligent lighting systems can dim or switch off entirely when spaces are vacant, then resume optimal settings as people enter.
• Demand-based scheduling ensures energy-intensive systems run only when required, avoiding waste during off-peak hours.

These automated adjustments not only cut unnecessary energy use but also reduce wear and tear on assets, lowering maintenance costs and extending their lifespan.

The role of sensor technology in driving efficiency

IoT sensors form the backbone of smart energy optimisation strategies, delivering granular, real-time insights into how buildings are used and how systems perform. By continuously capturing data from across a facility, they provide a level of visibility that traditional monitoring simply can’t match. This intelligence allows facilities teams to identify inefficiencies quickly, make informed decisions, and even automate responses to changing conditions.

Occupancy sensors, for instance, can feed live data into lighting, HVAC, and cleaning schedules. This ensures that resources are only deployed where and when they are needed, keeping empty rooms dark, reducing heating or cooling in unoccupied spaces, and prioritising cleaning for high-traffic areas.

Air quality monitors play a crucial role in maintaining both efficiency and occupant wellbeing. By tracking levels of CO₂, humidity, and other pollutants, they ensure that ventilation systems operate only as much as necessary to maintain healthy indoor conditions, avoiding the energy waste of over-ventilation.

Energy meters, particularly when installed at a zone or asset level, provide a detailed breakdown of where and how much energy is being used. This makes it easy to spot anomalies such as unexpectedly high consumption in a certain area, and target interventions more effectively.

Environmental sensors can also feed into predictive algorithms, enabling systems to make proactive adjustments before inefficiencies occur. For example, temperature and humidity data could trigger HVAC systems to adapt output in anticipation of a change in weather, rather than reacting after the fact.

When deployed strategically, sensors create a living, dynamic digital model of the building. This real-time picture empowers AI-driven platforms to make precise, timely recommendations, or even to trigger automated actions without human intervention.

Turning data into savings with AI

Smart building automation and sensors generate enormous volumes of data. AI can help turn that data into actionable insights.

Key ways AI reduces energy costs include:

• Predictive Maintenance: By spotting early warning signs of asset inefficiency, like a chiller using more power than usual, AI systems can trigger maintenance before the problem escalates, preventing both downtime and wasted energy.
• Optimisation Recommendations: AI can analyse historical performance, weather data, and occupancy trends to fine-tune system settings for maximum efficiency.
• Automated Decision-Making: In advanced setups, AI can directly control building systems, adjusting setpoints, schedules, and asset operation in real time without human input.
• Anomaly Detection: AI algorithms flag unexpected spikes in consumption so teams can act immediately.

As MRI’s James Massey explains:

“AI isn’t about replacing people. It’s about enhancing what they do, giving them better information, reducing admin, and helping them focus on higher-value tasks.”

Overcoming investment barriers

Even when the benefits are clear, budget constraints and concerns about future-proofing can delay investment in smart energy technologies. Many FM leaders worry about making large capital outlays for solutions that could be obsolete within a few years.

The key is to choose scalable, modular platforms that allow you to start small, focusing on the most impactful areas such as high-consumption HVAC or lighting systems before expanding over time. Focusing on integration and flexible licensing models also ensures the solution you select can grow and adapt with you over time, avoiding costly replacements in future and allowing you to scale intelligently as savings accumulate.

Real-world impact:

At MRI’s own London HQ, IoT-enabled monitoring feeds into AI-powered dashboards, optimising system performance for both energy efficiency and comfort. This has resulted in £20,000 annual savings, while supporting sustainability goals.

Similarly, clients like Arup are using MRI’s IoT Hub to combine people-counting sensors, air quality monitors, temperature sensors, and smart meters, generating actionable insights that drive operational efficiencies and measurable sustainability improvements. Click here to read the case study.

Driving energy, cost, and carbon savings

By combining automated control, real-time monitoring, and data-driven optimisation, facilities managers can unlock a continuous cycle of savings, resilience, and sustainability  without sacrificing occupant comfort.

The result? Lower energy bills, reduced carbon footprint, and buildings that work smarter every single day.

Visit our website today to learn more about how MRI’s smart energy management solutions can help your organisation.