Building Smarter: How AI Can Power a Greener Real Estate Future

As the global climate crisis intensifies, attention is increasingly turning to real estate — a sector responsible for nearly 40% of global greenhouse gas emissions. While traditional sustainability measures like energy-efficient lighting and green building materials are slowly becoming popular in real estate development, the integration of artificial intelligence (AI) and Internet of Things (IoT) technologies into buildings possesses even more potential for material financial savings and carbon reduction benefits. Buildings today are often powered inefficiently, leading to an over excess of carbon emissions. Heating, ventilation, and air conditioning (HVAC) systems blast at full force when spaces are empty, and lighting remains on regardless of occupancy. These practices waste energy and drive-up bills, particularly during peak times when the grid relies heavily on fossil fuels.

Predictive AI can help solve these issues by adjusting to energy demands dynamically. Real time data on weather, occupancy and grid conditions can be manipulated so that energy can be drawn from the grid at off peak times whilst it is cheap and clean. This process can be powered by AI or IoT (Internet of Things) and possesses material financial and environmental benefits, a viewpoint which is backed up by an array of evidence.

Recent studies suggest that AI-driven building management could significantly cut energy consumption in the coming decades. According to a study of over 87 educational properties in Stockholm, Sweden, HVAC systems are generally seen as a prime target for such energy optimization, as they typically consume between 35-65% of a commercial building’s energy. This same report found that AI-driven HVAC controls yielded an annual reduction of about 65 tons of CO2 emissions across the 87 properties, an impact which is approximately 60 times greater than the carbon emissions of running the AI system itself. All of these results frame AI as a tool that has already been effective in enhancing building sustainability.

There are also very impressive start-ups like Grid Edge and Brainbox which offer novel technology and the promise of exciting financial returns to the everyday consumer. Grid Edge in particular has developed AI to “predict energy demand and manage renewable integration in commercial buildings, shifting consumption to off-peak periods”. The key AI feature lies in the fact that machine learning is able to forecast an entire building's energy consumption and then automate the extraction, storage and distribution of renewable energy. With this, the company advertises a breakeven point within six months of purchasing and adopting the product. Moreover, the average carbon reduction for consumers is 20% at a minimum. BrainBox has also successfully implemented predictive AI to enhance efficiency in real estate developments. Their technology was integrated into HVACs on 45 Broadway allowing the property to draw energy from the grid at off-peak times saving costs of up to 25% and reducing carbon footprint by 40%. This data is incredibly exciting and speaks magnitudes to the volume of change that this technology can have in the real estate sector.

Whilst the current real estate technology landscape is dynamic and promising, carbon reduction technology has not penetrated the real estate market at the scale or speed required to make meaningful change. Currently, adoption is concentrated on premium commercial real estate assets where there’s stakeholder pressure, ESG mandates and most importantly the required capital to implement these technologies. It appears that the general sentiment surrounding carbon reduction technology in real estate is that it is nice to have rather than a baseline expectation or mandated outcome.

Importantly, financial incentives are key. Consumers and businesses are unlikely to adopt new technologies based on moral appeal alone. But when those same tools lower energy bills, and extend equipment lifespan while also reducing emissions the value proposition becomes undeniable as is the case with Grid Edge. There’s also a broader payoff. If AI were widely adopted across commercial real estate, the cumulative effect could help balance energy demand across the grid. That would reduce peak-time strain, cut energy prices, and make it easier to transition to renewables. In other words, smart buildings don’t just reduce their own emissions, but they make the entire energy system more sustainable.

The potential of AI in real estate is no longer speculative. The technology exists, the financial case is strong, and the climate stakes are higher than ever. Now, it’s up to developers, investors, and regulators to push adoption beyond niche markets. As the tools become more accessible and their benefits more visible, integrating AI into buildings should become an expectation. By embedding intelligence into our buildings, we’re not just optimizing systems but instead, reshaping cities to be cleaner, smarter, and more sustainable.

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Thomas Bartlett and Tanner Kelton are sophomores studying Philosophy, Politics & Economics at the University of Pennsylvania.