Generative AI is rapidly becoming embedded in commercial real estate workflows, promising faster analysis, fewer errors and round-the-clock productivity. But as firms lean into automation, a more complicated question is emerging beneath the efficiency gains. If entry-level work disappears, how does the industry train its next generation?
For decades, CRE talent development has followed a predictable path. New hires cut their teeth on foundational tasks such as underwriting deals, reviewing leases and analyzing operating data. That repetitive work has long been the gateway to deeper expertise. Now, many of those responsibilities are among the first to be automated.
"You look at an analyst who comes in and starts learning how to underwrite a deal," Adam Siegel, vice president of product strategy at Crexi, tells GlobeSt.com.
"So, they're reading the leases, they're reading the CAM recs, they're learning, and the only way they can do that is through repetition. You need to get hundreds of deals under your belt, thousands of leases under your belt. If those jobs go away — and I could see a world where they do — it's really going to change the landscape of how future investors or investment analysts get trained, because they're not going to be doing that basic level job. So, where do they start?"
That tension is becoming more visible as firms experiment with AI tools from providers like OpenAI and Anthropic. While the technology can accelerate early-stage analysis, industry leaders caution that speed does not equal judgment.
"AI is a phenomenal first draft," Jaime Sturgis, CEO of South Florida CRE brokerage Native Realty, tells GlobeSt.com.
"It is a terrible final answer. Someone with twenty years of scar tissue still has to look at the underwriting and say, 'That assumption is garbage.' The problem is that the person who's supposed to catch it is the same person we stopped training."
The concern is not just about individual deals but systemic risk. As firms layer AI onto complex real estate data, the margin for error can widen if human oversight erodes.
"AI cannot substitute for institutional knowledge," says Kumar Brahnmath, chief product and technology officer at Measurabl.
"The sector has too many asset-specific variables—leases, meters, utility data, building systems, local regulation, tenant usage patterns—for firms to assume a model can operate without human review."
Brahnmath warns that the industry could fall into what he calls a dangerous illusion of progress. "The biggest risk is 'automation theater,'" Brahnmath adds.
"A slick AI interface on top of bad data can produce faster, more confident wrong answers. In CRE operations, that can create problems for audits, investor reporting, regulatory filings, and capital planning."
Still, not everyone sees an immediate disruption to the workforce pipeline. Some executives argue that AI is reshaping junior roles rather than eliminating them outright.
Lauren Ball, chief operating officer at Westwood Financial, suggests the industry may be getting ahead of itself. "Replacing experienced professionals is still years away — AI today is a productivity layer, not a decision-maker," she says.
In practice, some firms are already rethinking how entry-level professionals are trained. Rather than focusing on manual production, younger employees are being pushed earlier into analytical and judgment-based work.
"The assumption is that if AI can do first drafts, junior roles disappear. In practice, we're seeing the opposite," explains Darrell Crate, CEO of Easterly Government Properties, a publicly traded REIT focused on acquiring, developing and managing Class A, mission-critical properties leased to U.S. government agencies through the General Services Administration.
"AI is automating repetitive tasks, but that allows younger professionals to spend more time understanding the 'why' behind decisions instead of just producing the paperwork."
That shift is already playing out in day-to-day operations at some companies. At Stuf Storage, AI handles much of the initial analysis, but the real work has moved upstream.
Katharine Lau, CEO of Stuf Storage, says AI is handling entry-level tasks such as research, data entry, and financial analysis.
"The 'doing' is no longer the work," she tells GlobeSt.com.
"The 'checking' is, and it's harder than what it replaced. For example, our revenue management agent will often suggest price and promo updates, but someone who knows the market has to sanity check whether they make sense. We put junior people on the verification work early alongside a senior expert, so they build market judgment by pressure testing the AI instead of doing the tedious work it replaced."
As AI continues to evolve, CRE firms are likely to keep recalibrating how they balance efficiency with expertise. The technology may streamline the industry's workflows, but it is also forcing a fundamental rethink of how knowledge is built, transferred, and sustained.
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