Schneider Electric, a prominent player in energy management and automation, is not only making strides towards its own sustainability goals but also empowering customers to enhance energy efficiency and slash emissions.

The company is on a clear path, guided by its Science Based Targets initiative-validated trajectory, to achieve a 25% absolute carbon reduction across its entire value chain by 2030 and reach net-zero CO₂ emissions across the value chain by 2050.

At the helm of the firm's global efforts to spur growth and innovation is Manish Kumar, Executive Vice President (EVP) of Digital Energy. With a mission to assist customers in digitizing and decarbonizing their operations, Manish brings nearly two decades of experience at Schneider Electric. His diverse roles have spanned corporate strategy, smart buildings, electrical distribution digitization, data centers, solar inverters, and microgrids. In this Q&A session, Manish shares his insights on decarbonization.

What Exactly Are AI-Enabled Buildings?

AI-enabled buildings are intelligent and interconnected structures that harness the power of AI and digital technologies. By leveraging data more effectively, these buildings optimize their operations.

They utilize real-time data from systems like HVAC, lighting, air quality, and occupancy sensors. This allows them to autonomously manage energy consumption, predict maintenance requirements, and enhance the comfort and well-being of occupants.

Through AI integration, these buildings transition from static assets to dynamic, "living" environments that continuously adapt to both internal and external conditions.

Sustainability of AI-Enabled Buildings

Amid the growing debate over the environmental impact of AI, its potential to drive sustainable operations should not be overlooked. When implemented thoughtfully, AI can have a significant positive environmental effect.

Buildings equipped with AI are inherently more sustainable compared to existing building stocks. They achieve this by maximizing energy efficiency and minimizing waste.

For instance, AI algorithms can analyze occupancy patterns and weather forecasts. Based on this analysis, they adjust heating, cooling, and lighting systems only when necessary, substantially reducing unnecessary energy consumption.

Moreover, these buildings support on-site renewable energy generation and storage, further reducing their carbon footprint. Schneider Electric's solutions have already helped clients cut carbon emissions by 15% and save up to US$10 million on green energy procurement.

AI-enablement is particularly valuable in complex, data-rich environments such as hospitals, airports, university campuses, large corporate offices, cities, and urban centers. In these settings, predictive maintenance, dynamic load balancing, and autonomous optimization can lead to measurable improvements in efficiency and resilience.

Influence on Energy Consumption

One of the most impactful applications of AI in buildings is in the realm of energy consumption. Real-time monitoring and predictive analytics in these buildings can pinpoint inefficiencies.

Once identified, facility managers can implement corrective measures and strategies. For example, Schneider Electric's research in Stockholm on AI-powered HVAC optimization in educational buildings resulted in an 8.93% reduction in electricity usage and a 259-tonne reduction in CO₂ emissions over four years.

Facility managers using AI-driven systems are already reaping tangible benefits in terms of energy savings, operational efficiency, and cost reduction.

The Energy Command Center

The Energy Command Center (ECC) is a centralized, AI-powered hub. It optimizes energy consumption across multiple assets within a building, or even across entire campuses and cities.

The ECC integrates data from HVAC, lighting, data centers, and other critical systems. It provides real-time monitoring, predictive maintenance, and seamless integration with existing infrastructure.

By transforming building operations from manual to autonomous, the ECC drives significant improvements in efficiency, sustainability, and cost savings. For instance, at Capgemini's 23 campuses in India, the ECC reduced energy consumption by 25 GWh and saved €3 million (US$3.5 million) while transitioning to 100% renewable electricity.

Impact of AI-Powered Cities on Citizens

AI-powered cities have the potential to greatly enhance the quality of life for citizens. By making urban infrastructure more efficient, resilient, and responsive, these cities can reduce energy costs, improve air quality, and ensure greater comfort and well-being for residents.

AI-driven systems can also assist cities in meeting ambitious climate goals, complying with regulations, and creating more sustainable and livable environments. Ultimately, by turning buildings and infrastructure into active participants in their own management, AI-powered cities enable citizens, businesses, and governments to collaborate more effectively towards a net-zero future.