The Moment of Change
Commercial real estate (CRE) is no stranger to disruption, but something different is happening now. The acceleration of consumer-driven artificial intelligence (AI) adoption is creating new demands on energy, data infrastructure, and cybersecurity, pushing CRE to a tipping point. Whether it’s Apple embedding AI into consumer devices or Microsoft integrating AI across workplace platforms, these shifts aren’t just about how businesses use technology—They’re about how buildings and portfolios will need to evolve.
What’s emerging is a fundamental rethinking of CRE strategy. The question isn’t whether AI will impact CRE, but how fast and how prepared the industry is to adapt. Owners, asset managers, and IT teams who act now will position their portfolios for long-term resilience. Those who wait risk being caught in an outdated model as tenant needs and infrastructure expectations shift beneath them.
AI’s Impact on CRE: The Convergence of Data and Buildings
The physical demands of AI, data center growth, and high-performance computing are accelerating at a scale few industries have fully grasped. We are seeing three major trends emerge, each pointing to an undeniable shift in how we use, manage, and value real estate.
First, the rising influence of data centers is redefining CRE investment. AI applications require enormous computing power, and this has driven record investment into new and expanded data centers. Large-scale developments, like the $2 billion-backed Novva Data Center in Utah, illustrate how AI-driven workloads are shaping the future of CRE. While some have floated the idea of repurposing office space for AI infrastructure, the reality is more complex. The cost, zoning hurdles, and power requirements make full-scale conversions unlikely in most cases. Instead, the opportunity lies in integrating AI-ready infrastructure and services within existing commercial spaces in a way that adds value rather than forcing a complete transformation.
Second, AI-driven computing is projected to massively increase electricity demand, creating an urgent need for more sophisticated energy management systems. Smart grids, battery storage, and onsite renewables will be essential for CRE owners looking to mitigate costs and reduce exposure to volatile energy pricing. The question is no longer whether AI will increase demand—It’s about how CRE portfolios will adapt to manage it efficiently.
Finally, AI isn’t just driving demand for data centers; it’s also changing how CRE is measured and optimized. Brookfield Infrastructure Partners is demonstrating how AI and data-driven insights are reshaping real estate investment. With the explosion of cloud computing and AI-driven workloads, Brookfield has made strategic bets on data center infrastructure, recognizing the long-term shift in how real estate assets generate value. Their acquisition of Compass Datacenters, in partnership with the Ontario Teachers’ Pension Plan, reflects a broader trend: real estate decisions are no longer just about physical square footage—they’re about data capacity, energy efficiency, and connectivity. Instead of relying on traditional asset classes, Brookfield is leveraging AI-powered analytics to forecast where digital infrastructure demand will grow, ensuring its portfolio remains resilient in the face of evolving market dynamics. This isn’t just about building more data centers—It’s about making smarter, more future-ready investment choices based on AI-driven insights into tenant demand, location viability, and long-term energy efficiency.
Goodman Group, an Australian-based global real estate company, is taking a similarly data-centric approach to real estate strategy, recognizing that the value of an asset is increasingly tied to its ability to support digital operations. Instead of viewing its industrial properties purely through the lens of logistics, Goodman has integrated AI-powered forecasting to identify which of its locations have the highest potential for data center conversion. The company has committed over $6 billion to new data center developments, including a $1.4 billion investment in Sydney. More than just an expansion play, this is an optimization strategy—Goodman is using AI-driven data models to determine which sites should shift from traditional industrial uses to high-value digital infrastructure. The result is a portfolio that is more adaptive, more resilient, and better positioned to serve the long-term needs of AI-driven enterprises. This shift underscores a growing reality for all CRE leaders: real estate decisions will increasingly be shaped by AI-powered analysis, optimizing for new types of demand rather than relying on outdated assumptions about space utilization.
What Comes Next for CRE
AI’s impact on real estate won’t be gradual—It will accelerate. The next five years will define which portfolios thrive and which struggle to adapt. Owners and asset managers who are serious about preparing for the future should focus on three key areas.
- Strengthening data and cybersecurity infrastructure: This must become a priority. Building operations are increasingly digital, and as AI-driven automation and tenant services expand, so do cybersecurity risks. A reactive approach won’t cut it. Owners need to assess vulnerabilities now, implement stronger protections, and work with experts who understand the intersection of cybersecurity and real estate.
- Rethinking asset strategies: Real estate leaders should be rethinking asset strategies to align with AI-driven growth. Instead of assuming office markets are in decline, consider how AI can create new demand for high-performance workplaces. Could hybrid spaces that integrate AI-enhanced collaboration hubs or automation-driven facilities become a new model for certain asset classes? Real-time utilization data will become a valuable tool for making smarter leasing decisions and optimizing asset positioning.
- Aligning AI readiness with energy and operational resilience: CRE firms need to align AI readiness with energy and operational resilience. Rising energy demands are unavoidable, but owners who proactively integrate AI-driven HVAC optimization, microgrids, and battery storage will reduce long-term costs and improve sustainability. The industry must start thinking beyond traditional utility models and instead design properties that can flexibly adapt to changing energy needs.
Final Thought: The Time to Act is Now
We are entering a new era where the intersection of AI, data centers, and real estate is reshaping the industry. This isn’t just speculation—It’s already happening. The companies that embrace AI-driven resilience, efficiency, and portfolio optimization today will be the ones that remain competitive in the years ahead.
AI’s rise is creating new opportunities, but those opportunities will only be realized by those who are ready for them. Real estate firms that invest now in data readiness, cybersecurity, and AI-enhanced operations will gain a competitive edge. Those that don’t will find themselves struggling to keep up as tenants, investors, and regulators raise their expectations.
If your organization is looking for guidance on navigating this transition, now is the time to develop a strategy.
The market is shifting—Will your real estate strategy shift with it?