Artificial Intelligence marks a decisive step towards a more efficient and responsible energy model. In the real estate sector, its application enables buildings not only to use less energy but also to learn, adapt, and continuously enhance the wellbeing of their occupants.
By combining real-time data analytics, predictive algorithms, and intelligent automation, resources can be optimized and energy needs anticipated, reducing both consumption and CO₂ emissions without compromising comfort.
From Reactive to Predictive Management
Traditionally, buildings operated under a static logic: climate and energy systems reacted to conditions as they occurred, with no capacity to anticipate change. Artificial Intelligence completely transforms this paradigm, enabling predictive management based on continuous learning.
Smart systems can now analyze variables such as weather patterns, occupancy levels, usage trends, thermal inertia, photovoltaic production, and consumption history to forecast thermal demand and adjust operations before changes happen.
The result: a more efficient, stable, and sustainable operation, where every kilowatt contributes to the planet’s wellbeing.
The Role of AI in the Energy Transition
As the global energy model moves toward flexibility and demand response, smart buildings play a leading role. With AI, they can adapt their energy consumption to real-time grid conditions, reducing impact during peak hours and taking advantage of cleaner or more economical energy periods.
This makes buildings energetically flexible assets, capable of actively contributing to the balance of the electrical system and to the broader goals of decarbonization.
oxxeo: A Real Example of Applied Smart Intelligence
In line with its commitment to sustainability and innovation, Gmp continues to advance the digitalization of its assets as the foundation for smarter, more efficient management.
At oxxeo, one of its most emblematic buildings, the integration of AI-driven tools has optimized energy performance reducing HVAC consumption by more than 25% and avoiding 49 tons of CO₂ emissions per year all while maintaining the highest standards of thermal comfort.
This model demonstrates how Artificial Intelligence, supported by data-driven strategies and digitalized assets, can turn information into sustainable decisions and drive continuous improvement in energy efficiency.
