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September 11, 2025
Digital Solutions: Using AI and Autonomous Control to Listen to Your Building
How can digitalization of the built environment positively impact operations and the climate? How can we combat rising energy rates and reduce carbon emissions? As we shift focus from equipment and services to outcome-driven demand, answering these questions is crucial.
Despite breakthrough innovation over the last several years, buildings still can’t speak to us. They do, however, constantly give us non-verbal cues through technologies like artificial intelligence (AI) and autonomous controls.
These solutions for digitalization of the built environment can significantly reduce a building's operating cost and its carbon footprint by allowing you to listen to its cues.
Thinking beyond trends
AI and autonomous controls are enhancing productivity, efficiency and decision making across every sector. Considering their applications in the built environment, it is easy to get excited about them.
As I've seen in my role as chief digital officer at Trane Technologies, AI and automation are being practically applied in HVAC systems to support outcome-based performance. And for good reason, as more than 50% of a building’s operating cost can be attributed to its heating, ventilation and cooling.
Implementing AI tools because they're trendy is faulty logic, though. Digital technologies require significant power and increase strain on our energy grids. They must be used thoughtfully and efficiently.
The true allure of digitalization and AI in the built environment lies in their ability to deliver operational cost savings, emissions reductions and optimal performance, which I see as their most discreet cool factor.
Listening to your building
Buildings can't speak, but they can send nonverbal cues, and "listening" to them is crucial.
AI technologies, like autonomous control systems, allow us to look at structured data (building layout, indoor temperatures, equipment specifications) and unstructured data (weather patterns and forecasts, pollution data, occupancy patterns) to optimize buildings’ energy performance.
AI-enabled building controls learn to respond to changing conditions, such as energy pricing fluctuations, to automatically optimize energy performance and enable cost-effective predictive maintenance.
Consider the analogy of streaming platforms, which regularly show new and interesting content, proving the value of monthly subscription fees. When we are satisfied with the programming, we may set them to auto-renew. But if the content becomes stale, we might start doubting its value and consider canceling. We need consistent performance to feel we're getting our money's worth.
The same mindset can be true for the built environment, but that’s also where digital enablement drives significant value—by reading and acting on a building’s non-verbal cues. Building automation systems and autonomous controls capture real-time data and advanced analytics and use them to optimize performance.
Leveraging these solutions can help building owners and operators understand their building operations while enabling energy and cost savings, demonstrating their ROI and economic viability.
In some cases, I've seen energy savings of 25% to 35% and paybacks of 12 to 18 months.
Creating successful outcomes from potential challenges
A comprehensive approach is required to implement digital solutions. To create your building's digital twin (a virtual representation of it), data requirements, computing capabilities and internal skills are factors to consider.
Data and information necessary to create a digital twin:
- Historical energy use
- Operational HVAC systems
- The building's architectural plans and layouts
You also need a robust cloud infrastructure to process large volumes of data, along with reliable and secure communication protocols for data transmission and storage.
More important than these elements, though, is a skilled talent pipeline that knows how to analyze data and machine learning techniques to find actionable insights and reduce latency. While innovative digitization technologies are changing the game for reducing energy demand and emissions across the built environment, prioritizing the talent to advance them is vital.
Of course, implementation can still bring challenges, including data integration and system interoperability. Integrating data from a variety of sources (sensors, historical records, occupancy and weather patterns) into a unified system can be complex and time-consuming. Different systems may also use varying formats, making it harder to standardize and harmonize data for analysis.
But these potential challenges can be turned into successful outcomes. Having a centralized platform capable of aggregating data into a single repository, where it is more easily accessed, managed and analyzed, is a critical component.
Transitioning from equipment to outcomes
Fifty years ago, the only thing customers cared about was the capital investment needed to install a high-quality HVAC system. Eventually, that progressed to high-quality and well-maintained systems, with good indoor air quality.
Today, things look drastically different. Customers demand outcomes, not just equipment that meets their day-to-day heating and cooling needs. They require high-quality, well-maintained, smart and adaptable machines that help reduce emissions, cut costs and optimize energy consumption.
This change in mindset affirms the growing demand for purpose-driven, sustainable technology that drives energy efficiency and decarbonization.
AI and digital technologies have the potential to harness the information provided by a building and its surroundings to achieve desired outcomes. This underscores the crucial need to pay attention and respond to the signals it’s sending.
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