In Commercial Real Estate, AI Is Compressing the Gap Between Small Operators and Institutional Firms

Written by:

Steve Marcinuk

Date:

02 Sep 2026

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The commercial real estate investment world has long operated on a simple asymmetry: large institutional firms like Blackstone and KKR can review hundreds of deals because they employ dozens of analysts, while smaller partnerships, two or three principals with limited staff, review far fewer, limiting their shot at finding the best opportunities.

That gap is narrowing. Nearly nine in ten CRE investors, owners, and landlords have now piloted some form of AI, and a majority of firms describe AI-driven analytics as central to how they evaluate deals, though a meaningful share of investment committees still say they distrust AI-generated underwriting outright.

The result is an uneven but accelerating shift: AI-powered underwriting tools are giving lean firms the capacity to screen deal flow at a pace that was previously only available to firms with deep payrolls.

Laura Krashakova, Founder & CEO of Smart Capital Center, one of several platforms building tools in this space, describes a shift in how her clients think about technology. Operators increasingly treat AI not as a back-office tool but as something that amplifies what their existing team can accomplish, functioning as a working partner rather than passive software. “They see AI and technology not only helping on the technology side, but really becoming real assistants in their work, and really helping them to amplify their existing team,” she says. “The existing team can do so much more now when they’re equipped with the right technology.”

The Bottleneck That Kept Small Firms Small

The math is punishing for lean operators in active investment mode. After fundraising from LP investors, a firm might need to review hundreds of deals to find the one worth a detailed underwriting and a bid. The other 99 represent time spent without return. When that screening is manual, Excel-based, and document-heavy, a small team hits a natural ceiling on deal flow, one that has historically tracked headcount almost one-to-one.

A handful of platforms now aim to break that link between headcount and deal capacity by generating draft underwriting, investment memos, and financing packages automatically. Smart Capital Center’s version of this is what Krashakova calls “AI analysts on demand.”

According to Krashakova, an analyst on her platform who previously reviewed five deals per week can now review 50, though independent surveys of CRE underwriting tools suggest results vary widely by firm and deal type, and document-extraction accuracy above roughly 95% is currently considered production-ready rather than universal. “Imagine how dramatically they broaden their scope,” Krashakova says. “All of a sudden they can start competing with those more institutionally funded companies.”

The output arrives as a digital environment rather than a spreadsheet or a Word file. Operators change assumptions in a few clicks and interact with the AI to pressure-test the numbers. The agents pull from borrower documents, market comparables, and sources across the web, then surface the patterns that sharpen the analysis. “Not just intuition-based and gut-feeling-based, but more data-rooted assumptions,” Krashakova says. “So this way it helps them not only to be able to do so much more, but also go much deeper, to have a much more disciplined approach about investing.”

Transaction Velocity Is Pulling Everyone In

The broader market effect is a compression of timelines across the entire transaction chain. As more parties, investors, lenders, brokers, adopt AI in their processes, those who haven’t are finding themselves forced into it by competitive pressure.

“Even if a certain operator may not necessarily be willing to use as much AI and automation in their processes, what we see is essentially they’re getting pulled into it; they’re getting forced, because if their competitors are moving faster, they also have to move faster,” Krashakova says. “Otherwise they’re just going to start losing the deals and losing returns that they were hired to grow.”

This dynamic extends to the lending side. Lenders are increasingly deploying AI not just for internal efficiency but as a signal to their own investors during fundraising: demonstrating AI-powered underwriting, origination, and portfolio surveillance gives LP investors confidence that an operator can manage risk and compete. “Oftentimes our prospective customers tell us, ‘We need to deploy by that day because we are starting our fundraising,'” Krashakova says.

A Lending Market That’s Cautious but Opening

Krashakova characterizes the current lending environment as “cautiously positive,” a mood she says is fairly constant among lenders but currently complicated by geopolitical uncertainty and rate policy. “I think we are getting out of the bottom in terms of property financial and operating performance, and ultimately that’s what drives lender interest,” she says.

Financing remains selective, especially for office and certain retail assets. At the same time, Krashakova sees opportunities in retail repositioning, high-quality office and industrial redevelopment, and select multifamily markets. San Francisco is one example: recent market reports show strong rent growth and falling vacancy, although estimates vary by data source and geography. “Commercial real estate is highly local. You have to understand the market, the property, and the business plan. A national trend alone cannot tell you whether a particular deal works,” she says.

The fragmentation of capital sources adds complexity. Beyond the major banks, hundreds of smaller credit funds have emerged in recent years with varying lending criteria. “Not everyone knows 500 other smaller credit funds that may have popped up in the last couple of years,” Krashakova says. Several digital platforms now aim to match borrowers to the right lending programs based on deal characteristics, addressing a common frustration: spending days or weeks communicating with a lending officer only to receive a rejection.

A borrower routed toward a higher-probability lender can avoid that cycle entirely, though the underlying matching quality still depends heavily on the platform and the data behind it.

The Workforce Divide

Krashakova identifies what she calls the “agentic revolution,” AI agents working alongside people, as the trend she believes is most underestimated in commercial real estate. The divide, in her telling, is not between firms that have AI and firms that don’t, but between individual professionals who master working with AI and those who resist it.

Krashakova believes the more meaningful divide will be between professionals who learn to work effectively with AI and those who continue to rely entirely on manual processes. In her view, the strongest results come when AI handles repetitive research and document work while experienced professionals direct the analysis, review the output, and make the final decision. “AI does not replace experience or judgment. It changes where people spend their time. The professionals who learn how to direct and review AI effectively will be able to contribute much more,” she says.

For commercial real estate professionals operating without large teams, the implication is direct: the tools that once separated a three-person partnership from an institutional firm are becoming more accessible, though far from evenly distributed or fully trusted yet. Firms that adopt them gain access to deal flow and speed they previously could not match.

Those that don’t face a market where competitors move faster, lenders increasingly expect digital workflows, and LP investors are starting to treat technology adoption as a baseline signal of competence, even as investment committees industry-wide remain split on how much to trust what the models produce.

About the Expert: Laura Krashakova is Founder and CEO of Smart Capital Center, an AI-powered underwriting and analytics platform serving commercial real estate investors.

This article is based on information provided by the expert source cited above. It is intended for general informational purposes only and does not constitute legal, financial, or real estate advice. Readers should conduct their own research and consult qualified professionals before making any real estate or financial decisions.