As artificial intelligence adoption accelerates, many commercial real estate investors are not accounting for the risks it poses to tenant businesses and long-term property values, according to Elon Gerberg, Co-Founder and Managing Director at Vision Real Estate Advisors.
While investors continue to focus on traditional indicators such as cap rates, occupancy, and rent growth, Gerberg warns that few systematically evaluate how AI could make certain tenant types less viable or reduce the workforce needs that drive office and retail demand.
“AI is something everybody needs to keep an eye on, and its impact across industries will be significant,” Gerberg says. He notes that questions about which jobs might be replaced or how efficiency gains could reshape business models are not receiving enough attention in investment analysis.
Gerberg explains that the main concern for property owners and investors is whether AI will render some business models obsolete and which tenants are most at risk. Retailers with labor-heavy service models, office tenants with large administrative staffs, and warehouse operators relying on manual processes could all face pressure as AI reduces human labor needs.
“If AI makes some businesses obsolete, investors need to know which tenants are vulnerable,” Gerberg says. The risk is not limited to individual businesses. If AI adoption reduces workforce needs, office demand could fall even in growing markets. Retail tenants relying on large staffs may struggle if competitors adopt AI tools that cut labor costs.
Gerberg points out that a tenant who seems stable today could face challenges in a few years if competitors use AI to lower costs or if consumer preferences shift toward automated services. Standard lease and credit analyses do not capture this risk.
Gerberg sees the industry at the start of a major transition, with AI adoption effects still uncertain. He compares it to tectonic plates moving slowly but eventually causing major changes. “We’re in the early stages, and nobody really knows for sure how it will play out,” he says.
This uncertainty complicates due diligence. Traditional underwriting focuses on current tenant credit, lease terms, and market fundamentals, but these measures may not reveal whether a tenant’s business model can withstand rapid technological change. A tenant with strong financials today could see revenue decline and eventually default if AI disrupts their sector.
For landlords, the risk is heightened by long-term leases. A tenant signing a 10-year lease may appear secure now, but if AI changes their industry within five years, the property could face a struggling or defaulting tenant.
The effects of AI adoption vary by property type:
Gerberg advises investors to evaluate which tenant types are most exposed to AI-related disruption and consider portfolio concentration. Properties with diverse tenant mixes may be more resilient than those heavily reliant on a single industry.
Gerberg argues that commercial real estate investors need new frameworks to evaluate technological risk. Relying only on backward-looking financials ignores the possibility that AI could quickly erode tenant businesses.
“Investors need to ask which jobs are likely to be replaced and how efficiency gains will reshape tenant demand,” Gerberg says. Most investors are not yet accounting for AI risk in underwriting, but this will change as technology’s impact becomes visible. By the time disruption is obvious, property values may already have adjusted, leaving unprepared investors with depreciating assets.
Vision Real Estate Advisors, co-founded by Gerberg and Adam Klein nine months ago, focuses on retail, office, and industrial properties in South Florida priced from $2 million to $25 million. The firm has closed about $70 million in transactions and manages roughly $80 million in exclusive listings.
Gerberg says the firm closely monitors AI developments and their effects on tenant viability and long-term demand. While South Florida’s population growth and limited supply help insulate property values, technological disruption could create challenges that demographics alone cannot solve.
As AI adoption accelerates, commercial real estate investors need new ways to evaluate tenant risk and stress-test portfolios for scenarios in which technology changes demand for physical space. Investors who adapt their analysis will be better positioned to navigate a market where traditional metrics no longer fully capture the forces shaping property values and tenant stability.
In the coming years, the ability to anticipate AI-driven changes may separate successful investors from those caught off guard. Relying solely on historical data and established underwriting practices may leave investors exposed to emerging risks as AI reshapes tenant viability.
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