Board Series: Real Estate’s AI moment – opportunity and uncertainty

Key takeaways

• AI is being implemented and use across the real estate value chain, enabling smarter buildings, better forecasting, and more responsive operations; and real estate players connected to the data center boom are already seeing surging demand.
• The growth of AI is straining utilities and construction resources, driving up energy costs and disrupting supply chains which are critical to real estate developments; and long-term shifts in ways of working driven by AI may have sweeping impacts on demand for office and retail real estate.
• Boards must act with foresight and balance, championing the strategic use of AI while embedding resilience into capital planning, supply management, and ESG governance.

AI in Real Estate: The Upside

AI is proving to be a tectonic force across the real estate value chain. Early adopters are seeing tangible improvements in everything from operational efficiency to tenant satisfaction and investment returns. Key benefits include:

• A data center boom: For real estate companies connected to data center and digital infrastructure, AI is unlocking significant growth. By some estimates, the demand for data center capacity globally could potentially triple by 2030. This surge in demand for data centers has driven up land values and lease rates across primary and secondary markets, especially in those with strong power and fiber connectivity.
• Smarter operations: AI-powered building systems now optimize lighting, HVAC, and maintenance based on real-time usage, significantly reducing costs and emissions. A wide range of intelligent building management systems and software have sprung up to help operators manage their buildings more efficiently, leading to as much as a 30% improvementin energy efficiency. For certain subsectors, like data centers or warehousing & logistics, where a majority of OpEx can come from heating, cooling, and lighting the building, this can translate into real impact for the bottom line.  
• AI-driven Proptech: A whole host of tools and solutions have come onto the market which leverage AI for everything from creating digital twins to conducting energy simulations and developing proprietary advertising solutions. Odyssey, for example, is an AI-powered platform which allows building owners and operators to create energy efficiency roadmaps from as little as an address and enables them to capture savings as high as $4.65 / sqft. in healthcare buildings, $1.90 / sqft. in multifamily, and $1.67 in manufacturing & industrial.
• More accurate forecasting: Predictive analytics are improving underwriting and investment decisions significantly, helping companies better understand tenant demand, market cycles, and portfolio risk.
• Faster, smarter development: Generative design tools are accelerating site planning and maximizing space utilization, while AI-enabled tools streamline lease abstraction and automate compliance workflows.
• Personalized tenant experiences: AI is powering leasing platforms that adjust marketing and pricing strategies dynamically, improving conversion rates and lease-up timelines. For real estate players in the multifamily and office subsectors, this can mean significant opportunities to capture new value and reduce operating costs.
• Portfolio-wide retrofit planning: With 80% of U.S. commercial buildings built before 2000, AI is transforming how owners plan large-scale retrofits by identifying where interventions will yield the highest return. For older and large buildings, like multifamily properties in coastal cities, this can unlock enormous time savings, preventing the need for extensive onsite engineering visits.

The implications aren’t just operational — they’re strategic. Companies using AI effectively are seeing reduced operating costs, faster lease-up rates, and smarter capital deployment. For example, AI is helping property managers forecast maintenance needs before problems arise, reducing costly equipment failures and tenant complaints. In the investment arena, AI-driven tools can analyze market trends, tenant behaviors, and economic indicators to guide better decisions about acquisitions and divestments.

Even how building components are being handled at end-of-life is changing. As smart building systems and data management technologies are spreading, building owners and operators are getting far smarter about how to anticipate and plan for cost-saving retrofits through AI-powered tools. Before, the task of planning the replacement of tens of thousands of components across thousands of aging buildings was costly at best and nearly impossible at worst. Today, AI greatly enhances the ability of real estate players to maximize retrofit investments across their portfolios.

AI’s Emerging Downsides: What boards must consider

For all the momentum, AI’s rise is not without costs — and in many cases, those costs are being paid by adjacent sectors like real estate. As boards weigh the value of AI investments, they must also account for potential downsides:

• Skyrocketing energy demand: After years of relatively flat or even modestly declining electricity demand in the US, AI infrastructure — especially hyperscale data centers — is igniting explosive growth in energy demand. By some estimates, the electricity needed by data centers globally could reach 945 terawatt-hours by 2030, which is equivalent to the total consumption of the country of Japan today. In some regions, the energy demand pressure from AI-related activities is already quite acute. In places like Northern Virginia (sometimes referred to as “Data Center Alley”), data centers are siphoning off the power needed for residential and commercial growth, complicating green energy transitions and driving up utility costs. For certain commercial real estate users for whom affordable electricity is vital the bottom line, like industrial and manufacturing, this poses significant risks.