LOW CARBON HEATING & HVAC
Traditional approaches to HVAC management are no
longer enough. Sadiq Sayed, SVP Digital Energy Software Business at Schneider Electric, examines how AI is enabling buildings to become ‘living systems’ that tune themselves for greater efficiency, comfort and resilience
C
ommercial buildings still rely on HVAC to maintain comfort and indoor air quality, but
the operating context has changed materially over the last few years. Higher energy prices, increased scrutiny of operational carbon, and tightening expectations around compliance, are forcing estates teams to account for performance in use, not simply design intent. For sustainability leaders, energy managers and facilities directors, the question is increasingly practical: which interventions can be delivered across a live estate, what internal resource is required to sustain them, and how quickly outcomes can be evidenced. AI-driven HVAC optimisation is often presented as
a software layer, but in practice it succeeds or fails on the strength of sustainability solutions. The approach combines existing BMS data with additional metering and sensing where needed, then applies analytics to improve scheduling and setpoints, identify control conflicts, and detect faults earlier. Done properly, the benefits are material: lower
energy consumption, more stable control, fewer complaints, earlier identification of degrading components, and fewer avoidable call-outs.
FROM ‘SET-AND-FORGET’ CONTROL TO OPERATIONAL CARBON MANAGEMENT Traditional approaches to HVAC management are no longer enough. Most commercial buildings still operate on fixed schedules and static setpoints, with little consideration for real-time occupancy, weather fluctuations, or equipment health. Over 30% of HVAC consumption is estimated to be unnecessary, resulting in wasted energy and missed opportunities for optimisation. At the same time, facility teams are being asked
to do more with less. The building technology skills gap is widening, regulations are tightening, and there is an increased need for more flexible spaces in line with changing business needs. In this context, AI-powered HVAC optimisation is not just a technological upgrade, it’s non-negotiable.
WHAT OPTIMISATION DELIVERS AI brings a new level of intelligence to HVAC operations. By continuously analysing data from sensors, weather feeds, occupancy patterns, and asset health, AI algorithms can predict and adjust system behaviour in real time. They learn the unique rhythms of each building, predicting demand and proactively adjusting setpoints, ventilation rates, and equipment operation. Over time, the AI
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HOW AI BRINGS A NEW LEVEL OF INTELLIGENCE TO HVAC OPERATIONS
By continuously analysing data from sensors, weather feeds, occupancy patterns, and asset health, AI algorithms can predict and adjust system behaviour in real time
engine refines its models, learning from every data point to optimise performance. This optimising shift from reactive to adaptive is transformative. Buildings become living systems, continuously tuning themselves for efficiency, comfort, and resilience without constant human oversight.
GETTING THE FOUNDATIONS RIGHT AI-powered HVAC optimisation is built on a comprehensive technology stack. At the core are BMS, which serve as the nerve centre, aggregating data from HVAC equipment, sensors, smart meters, and other building systems. This foundation enables centralised control and monitoring and is essential for AI integration. Digital twins, or virtual replicas of buildings, are
continuously updated with real-world data. AI models simulate HVAC operations within the digital twin, allowing facility managers to test scenarios, predict outcomes, and identify optimal parameters, without impacting actual operations. Digital twins are invaluable for risk-free experimentation and long-term planning. Real-time data integration is another critical
component. AI engines ingest data from a wide range of sources, and this continuous data flow enables real-time decision-making, fault detection, and predictive maintenance. Hybrid architectures that combine the strengths of cloud and edge computing are becoming more
ENERGY & SUSTAINABILITY SOLUTIONS - Summer 2026
common. Cloud AI handles large-scale data aggregation and complex analytics, while edge AI delivers real-time responsiveness at the device level. This balance ensures both portfolio-wide optimisation and immediate, local control. Finally, intuitive dashboards and mobile apps
empower facility teams with actionable insights, alerts, and performance metrics. Automated work orders, fault diagnostics, and energy analytics streamline operations and simplify maintenance, making advanced HVAC management accessible to teams of all sizes.
HOW TO SCALE FROM PILOTS TO PORTFOLIO-WIDE SAVINGS Scaling starts with a site audit: controls capability, plant condition, and metering coverage. From there, establish a reliable data layer with calibrated sensors, consistent tagging, and defined trend intervals. A credible approach sets KPIs for energy, comfort and stability, specifies measurement and verification, and defines roles for seasonal tuning and recommissioning. Buildings change over time, and optimisation
must be maintained accordingly so that initial improvements become sustained, auditable operational gains rather than short-lived pilot results.
Schneider Electric
www.se.com/ww/en
www.essmag.co.uk
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