CPE Executive Council: Where AI Creates the Best Value for CRE
Applications that are driving better decisions, greater efficiency and stronger returns.
AI has plenty of applications for real estate. But to find out the best uses, you have to also sort through what’s frivolous, a fad, or just a waste of time. This month the CPE Executive Council cuts through the noise and shares where AI is the most valuable for commercial real estate.
Better Predictions
The biggest value AI will unlock in commercial real estate is better prediction on high-stakes decisions—especially underwriting, tenant risk, lease intelligence and portfolio strategy. These are areas where there’s enormous unstructured data, real capital at risk, and real information asymmetry. When you improve prediction there, it shows up directly in better risk-adjusted returns and faster deal execution.
For me, the highest-leverage application is tenant risk prediction and renewal underwriting—particularly in single-tenant net lease. Today, underwriting leans heavily on tenant credit ratings and gut-level judgment about renewal probability. AI models trained on historical retailer performance, combined with location-level data such as demographics, traffic patterns and even sentiment from filings and news, can produce a much sharper, asset-by-asset read of renewal versus closure risk.
That matters because it prices near-term lease-expiration risk more accurately, rather than over-discounting good assets out of caution—and it gives owners an earlier read on which tenants are actually vulnerable, before it shows up in the numbers. Deloitte’s 2026 CRE Outlook lists tenant relationship management as one of the industry’s top AI priorities over the next 12 to 18 months, and I think that’s exactly right—the firms that get ahead of this now will have a real pricing edge before the rest of the market catches up. —Randy Blankstein, President, The Boulder Group
Eliminate Friction
I think the biggest misconception in CRE is that AI’s greatest value will come from predicting rents, cap rates, or property values.
The largest near-term value creation is eliminating friction from information-heavy workflows, while the largest long-term value creation comes from improving capital allocation decisions.
A recent internal CRE economics piece argues that the clearest AI impact today is showing up through productivity gains, particularly in industrial facilities and data centers, rather than through dramatic changes in property fundamentals. Meanwhile, institutional firms are increasingly deploying AI across underwriting, research and asset management workflows.
If I were presenting this to an investment committee, I’d rank the opportunity as:
Rank Area/Value Creation Potential
- Underwriting & investment decisions/Very High
- Asset management & NOI optimization/Very High
- Research & market intelligence/High
- Lease/document abstraction/High
- Property operations & maintenance/Moderate-High
- Brokerage & leasing productivity/Moderate
- Valuation forecasting/Moderate
The greatest value in CRE won’t come from AI predicting the future better. It will come from compressing the time between data, decision and action.
For investors, that means better underwriting and capital allocation.
For operators, that means higher NOI through revenue optimization and expense control.
And at the macro level, the biggest physical-property beneficiaries appear likely to be data centers, modern logistics facilities, and advanced manufacturing assets, where AI is directly increasing demand rather than merely improving productivity. —Doug Ressler, Manager, Business Intelligence, Yardi
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