Artificial intelligence is no longer a futuristic concept for commercial real estate. Across the industry, AI is moving from pilot programs and conference-room demonstrations into everyday workflows — helping brokers research properties, investors evaluate deals, owners manage buildings and property teams respond to tenants.
Arizona offers a particularly interesting lens through which to view that transformation. The state’s commercial real estate market spans fast-growing industrial corridors, a massive multifamily development pipeline, a recovering office sector and an increasingly growing data-center industry. At the same time, those sectors generate enormous amounts of information — exactly the kind of environment where AI can provide an advantage.
For investors, one of the most immediate applications is deal analysis. AI can rapidly organize leases, operating statements, market reports, property records and comparable sales, allowing investment teams to spend less time gathering information and more time evaluating what it means. CRE technology companies are now embedding AI directly into underwriting, offering memorandums and transaction workflows. Crexi, for example, introduced a suite of AI tools in 2026 designed to accelerate tasks ranging from document creation to deal analysis, streamlining workflow and rapidly providing data.
That shift is especially relevant in Arizona, where investors are evaluating very different opportunities within the same state. Greater Phoenix ended 2025 with improving fundamentals in several major sectors. Industrial vacancy fell to 9.7%, while the office market recorded its strongest quarterly net absorption since 2019. Multifamily, meanwhile, continued to attract investment even as substantial new supply put pressure on occupancy and rents.
AI can help investors make sense of those competing signals. Rather than simply asking whether Phoenix industrial is performing well, an investor could use AI-assisted analytics to compare submarkets, tenant concentrations, lease expirations, transportation access, construction pipelines and demographic trends. The result isn’t necessarily a better prediction; it is a faster and broader way to develop the assumptions behind an investment decision.
Property operations are another area where AI is becoming practical. Large commercial real estate firms are using AI to identify operational problems, analyze building data, automate reports and anticipate maintenance needs. JLL, for example, describes AI applications that can predict equipment failures, manage work orders and analyze portfolio performance. Its Property Assistant can also generate financial insights, create leasing-related materials and answer questions using building-operations data.
For Arizona owners, this could have particular value in managing large, geographically dispersed portfolios. A property manager overseeing assets in Phoenix, Tucson, Scottsdale, Tempe and the East Valley can use AI to surface outliers and prioritize issues rather than manually reviewing every data point. The technology doesn’t eliminate the property manager; it potentially allows that person to focus more time on tenants, vendors, negotiations and asset strategy.
AI is also changing the physical real estate landscape. Arizona has become an important market for data-center development, and the relationship between AI and real estate is unusually direct: The same technology driving AI adoption is creating demand for specialized buildings, power infrastructure and land.
There is, however, a cautionary side to the technology. AI is only as reliable as the information and assumptions behind it. Confidential leases, financial information and proprietary investment strategies also raise obvious questions about data security. And an AI-generated answer can sound authoritative while still being wrong. The information fed into AI should also be treated with the “garbage in, garbage out” thought process. If the information fed into it is bad or not fully vetted, the result can also be expected to be poor.
That makes human expertise more — not less — important. CBRE has emphasized that AI can enhance decision-making while keeping people in the loop, while JLL’s research shows that AI adoption is accelerating but many organizations remain in the experimentation phase.
For Arizona’s CRE community, the competitive question may therefore not be whether AI will replace brokers, investors, developers or property managers. It is whether professionals who know how to use AI effectively will outperform those who do not.
The technology is already here. In a market as diverse and rapidly changing as Arizona, the advantage may belong to the professionals who can combine AI’s ability to process massive amounts of information with something technology still cannot fully replicate: local knowledge, relationships and judgment. But as Mark Cuban stated, “If your competitor is using AI and you are not, they are moving at the speed of light while you are walking.”
Kim Ryder is a dynamic commercial real estate executive with extensive experience in managing multi-million-dollar, complex projects and the build-out of more than 54 million square feet of retail and commercial space. Ryder has started several business lines in her career, most notably launching Thrive Real Estate and Development groups. Her career in the thrift industry extends over 25 years and led her team to expand the Goodwill real estate portfolio by more than 100 locations, having leadership over more than 400 transactions. Her expertise in thrift real estate has made her a well-known resource.
