Schneider Electric Q&A: How AI Buildings Cut Energy Use

Schneider Electric is making progress against its sustainability targets while helping customers improve energy efficiency and cut emissions. 

The energy management and automation firm reports transparent advances towards a 25% absolute carbon reduction across its entire value chain by 2030 and net zero CO₂ across the value chain by 2050, guided by its Science Based Targets initiative validated trajectory.

Manish Kumar, Executive Vice President (EVP) of Digital Energy, leads the firm's global efforts to drive growth and innovation with a mission to help customers digitalise and decarbonise their operations.

With nearly two decades at Schneider Electric, Manish has held roles spanning corporate strategy, smart buildings, electrical distribution digitisation, data centres, solar inverters and microgrids.

Manish shares his decarbonisation knowledge in this Q&A.

What are AI-enabled buildings?

AI-enabled buildings are intelligent, connected structures that leverage AI and digital technologies to optimise their operations through better use of data. 

These buildings use real-time data from systems such as HVAC, lighting and air quality and occupancy sensors to autonomously manage energy consumption, predict maintenance needs and enhance occupant comfort and well-being. 

By integrating AI, these buildings transform from static assets into dynamic, “living” environments that continuously adapt to both internal and external conditions.

How are these buildings sustainable?

While there’s growing discussion around the environmental footprint of AI, it’s important to recognise the powerful role it can play in driving sustainable operations.

With thoughtful implementation, AI can be a force for positive environmental impact that we shouldn’t overlook. 

Using AI in buildings makes them inherently more sustainable than existing building stock.

This is because they maximise energy efficiency and minimise waste. 

For example, AI algorithms can analyse occupancy patterns and weather forecasts to adjust heating, cooling and lighting only when needed, significantly reducing unnecessary energy use.

These buildings also support on-site renewable energy generation and storage, further lowering their carbon footprint. 

In fact, our solutions have helped clients reduce carbon emissions by 15% and save up to US$10m on green energy procurement.

AI-enablement adds significant value in complex, data-rich environments such as hospitals, airports, university campuses, large corporate offices, cities and urban centers where predictive maintenance, dynamic load balancing and autonomous optimisation can drive measurable efficiency and resilience.

How can AI-enabled buildings influence energy consumption?

One of the most influential areas of using AI in buildings is in the energy consumption space. 

The use of real-time monitoring and predictive analytics in these buildings can identify inefficiencies. 

Once issues are identified, facility managers can implement fixes and strategies to improve the situation.

Take for example, our research in Stockholm on AI-powered HVAC optimisation in educational buildings. 

It led to 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 seeing tangible benefits in energy savings, operational efficiency and cost reduction.

What is the Energy Command Centre?

The Energy Command Center (ECC) is a centralised, AI-powered hub that optimises 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, providing real-time monitoring, predictive maintenance and seamless integration with existing infrastructure. 

By transforming building operations from manual to autonomous, the ECC drives measurable improvements in efficiency, sustainability and cost savings. 

For example, at Capgemini’s 23 campuses in India, the ECC reduced energy consumption by 25 GWh and saved €3m (US$3.5m) while transitioning to 100% renewable electricity.

How can AI-powered cities affect citizens?

AI-powered cities have the potential to greatly enhance the quality of life for citizens by creating healthier living and working spaces. 

By making urban infrastructure more efficient, resilient and responsive, these cities can reduce energy costs, improve air quality and ensure greater comfort and wellbeing for residents. 

AI-driven systems can also help cities meet ambitious climate goals, comply with regulations and create more sustainable, liveable environments. 

Ultimately, by turning buildings and infrastructure into active participants in their own management, AI-powered cities empower citizens, businesses and governments to collaborate more effectively towards a net zero future. 

We’re also only really at the beginning of this revolution.

While we’ve talked about prosumers for years, we’ve found growing interest from consumers around installing their own solar panels, for example and integrated smart home controls through AI-powered decision making makes this investment far more valuable. 

Consumers will then be able more readily participate in smart city programmes as they can sell energy back to the grid seamlessly.