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Artificial Intelligence is reshaping real estate—from the surge in data center development to the rise of intelligent energy systems and generative design. This technological leap offers a way to accelerate decarbonization and boost operational performance. But it also brings new strains: greater energy demand, more complex supply chains, and heightened uncertainty in long-term planning. As AI becomes embedded in the built environment, will real estate leaders step up to make sure innovation drives sustainability, and not just scale?
AI in real estate: The upside
AI is proving to be a catalyst for energy efficiency, carbon tracking, and asset optimization — especially in older and energy-intensive buildings. Key benefits include:
- Demand for data centers surges. For real estate companies connected to data centers and digital infrastructure, AI is unlocking significant growth. By some estimates, the demand for data center capacity globally could triple by 2030. This surge in demand for data centers has driven up land values and lease rates across primary and secondary markets.
- Smarter operations and cost savings. AI-enabled systems optimize HVAC, lighting, and maintenance in real-time, improving energy efficiency by up to 30%. For high-intensity assets like data centers and logistics facilities, this can translate into substantial cost savings and significant emissions reductions. A host of tools and solutions have come onto the market which leverage AI for everything from creating digital twins to conducting energy simulations. 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.
- More accurate market analysis. Predictive analytics are improving underwriting and investment decisions significantly, helping companies better understand tenant demand, market cycles, portfolio risk, and due diligence.
- Harmonizing portfolio-level strategies with individual asset 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 – both monetary and in terms of emissions.
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. 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.
AI’s emerging downsides
For all the momentum, AI’s rise is not without costs. As real estate leaders weigh the value of AI investments, they must also account for potential downsides:
- Energy capacity constraints and increased costs due to skyrocketing 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 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.
- Resource competition. AI’s explosive growth is tightening supply chains for construction materials, electrical components, and skilled labor. Real estate developers are increasingly being outbid by AI-focused firms offering speed and premiums to accelerate their own construction.
- Potential AI-bubble burst. Markets with accelerated data center deployments and technological hubs (like San Francisco or Seattle) are likely to experience a disproportionately high increase in real estate demand in the short-term. However, there is considerable risk of AI-related hype slowing down, or even reversing, leaving players in these markets exposed.
- Fake AI solutions. Several companies have been identified as merely pretending to offer AI-driven prop tech solutions, exploiting the current favourable market sentiment towards artificial intelligence. For example, Opendoor agreed to pay $39 million to settle a securities lawsuit alleging that it misled investors about the capabilities of its purportedly AI-powered home-pricing algorithm. Thoughtful and thorough due diligence is essential before piloting and adopting such solutions.
Strategic priorities for real estate leaders
Real estate leaders have a pivotal role to play in navigating the sector’s AI moment — not just in identifying the upside, but in planning for the systemic risks AI introduces. Here’s where to focus:
- Understand how growth of AI will impact operations and strategy. Ensure that strategies account for rising energy costs, community sentiment around data center expansion, shifting demand around tech hubs and potential energy capacity challenges. Real estate leaders should push for scenario planning that incorporates grid stress, rising utility rates, and ESG implications.
- Leverage AI tools to identify quick operational wins. Prioritize AI deployments that deliver fast and measurable emissions reductions, energy savings, or resilience benefits. Focus on scalable applications like energy modeling, retrofit optimization, predictive maintenance, and even recruitment efforts.
- Embed AI tools into capital planning and due diligence processes. Use AI to identify the highest-impact retrofits across the portfolio, especially for aging assets. Integrate AI into climate resilience strategies, particularly flood, heat, and grid-stress scenarios.
- Create AI governance and safeguards. Ensure AI initiatives meet data privacy, equity, and governance standards. Real estate leaders have a key role in shaping the ethical deployment of AI, especially where it touches tenants, communities, and employees. A key factor to consider in any data strategy is deploying strict controls over data access.
A few considerations for real estate leaders:
- How are you monitoring the energy and carbon impact of AI infrastructure across your portfolio?
- How are you collaborating across teams to ensure AI enhances, rather than competes with, sustainability priorities?
- Are AI-related investments aligned with your sustainability roadmap and/or net-zero targets?
AI is changing the rules—and the risks—for real estate. Telesto Strategy is helping leaders harness AI not just for performance, but for long-term resilience and sustainability. Let’s talk about how you can put it to work across your portfolio.
Our people
Andrew Alesbury
Partner, Washington DC
With a background spanning both urban planning and private real estate development in the United States and Middle East, Andrew supports real estate investors and other firms with large portfolios of physical assets to create sustainable strategies which integrate resilience and sustainable risk management into their business models and investment processes.
Ben Vatterott
Partner, San Francisco
Ben has led sustainability and growth strategy projects for clients across the real estate ecosystem, including investment firms, construction materials manufacturers, PropTech companies, and more. He supports clients on a number of strategic topics such as setting net zero targets, embedding sustainability and emissions reduction into capital deployment, and capturing sustainable growth opportunities.
Diego Bernstein
Manager, Miami
Diego helps real estate practitioners implement their sustainability strategies including net zero roadmaps, climate risk strategies, building economic models, demonstrating his expertise in renewables and sustainable technologies.
