AI Just Changed How Commercial Real Estate Deals Get Done. Here’s What It Means for You

Written by:

Alejandra Rodriguez

Date:

06 Apr 2026

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If you’ve toured a property, applied for a loan, or signed a lease recently, you likely interacted with artificial intelligence (AI) without realizing it. In commercial real estate, AI now works behind the scenes to speed up property searches, flag risks, and generate listing materials. What was once a buzzword is now a practical tool shaping how deals are made from the first search to the closing signature.

James Huang, Managing Director of Commercial Real Estate at RESAAS Services Inc., has spent more than 30 years in the industry, witnessing technology’s evolution firsthand. He started in the 1990s, when fax machines were standard. Now, he helps brokers and investors navigate a landscape where AI can analyze thousands of properties in seconds, automate loan approvals, and quickly identify market trends.

“The way you do real estate keeps changing,” Huang says. “AI is even changing things more, and really embracing and understanding AI is critical now.”

But while AI brings speed and efficiency, it also introduces new risks, such as errors that go unchecked or hidden bias in algorithms. Here’s how AI is changing commercial real estate today – and what you should know before your next deal.

Search and Discovery

AI-powered search tools have moved beyond basic filters. Today, you can describe what you want – such as “mixed-use building near transit, under $2 million, with strong foot traffic” – and receive listings that genuinely fit those needs. These tools learn from transaction data to interpret terms like “walkable neighborhood” or “high visibility,” saving time on irrelevant options.

However, AI lacks local context. A property might meet all technical criteria but be located next to a noisy site or have a history of tenant disputes – details a local broker would catch, but an algorithm might miss.

Pricing and Valuation

AI pricing models use recent sales data and market trends to estimate property values and suggest optimal listing times. For sellers and landlords, this means more accurate pricing and potentially faster deals. For buyers and tenants, AI can help spot overpriced listings.

Still, these models depend on the quality of their data. Outdated or incomplete information can lead to inaccurate price estimates. “AI can crunch data, but it can’t tell you why a street just feels off or why a property gets no offers,” Huang says. Local expertise remains essential, and human appraisers or brokers should always review major decisions.

Faster Approvals, Broader Access

AI-driven underwriting has dramatically sped up loan approvals. Some lenders now use AI to assess nontraditional income, such as freelance work or rental earnings, opening new opportunities for investors and self-employed buyers who previously didn’t fit standard criteria.

But this speed comes with risks. AI can overlook context that a human underwriter would catch, such as a temporary drop in income due to planned leave. If you’re applying for financing, review your credit and financial records ahead of time and be prepared to explain any unusual entries.

Marketing and Listings

AI now automates listing descriptions, photo selection, and even virtual staging. This makes for polished, fast listings, saving time and money for landlords and sellers. However, AI-generated content can sound repetitive and sometimes gloss over property flaws. A listing might downplay maintenance issues or use vague language to avoid red flags.

Buyers and tenants should read carefully and ask for specifics. Request maintenance records, inspection reports, or a live tour to get a full picture beyond what AI provides.

Screening and Leasing: Efficiency with Potential Pitfalls

Landlords use AI to screen applications and automate background checks, reducing vacancy periods and administrative work. For tenants, this means quicker responses, but also the risk of unfair rejection. AI screening tools have drawn criticism for reflecting bias based on zip codes, names, or data errors.

If your rental application is denied, you have the right to request the reason and a manual review to correct any mistakes.

Where AI Delivers and Where It Falls Short

AI can save days or weeks in the property search, financing, and leasing process. It uncovers options that older search methods might miss and provides more data for pricing and timing decisions. But AI still struggles with the human factor – local quirks, property histories, and subtle warning signs. It can also introduce or perpetuate bias and make mistakes that only a human can catch.

For example, an AI screening tool once flagged a renter as high-risk due to a data error, costing them an apartment until a human reviewed the case and corrected it. While rare, these errors highlight the need for human oversight.

How to Use AI Wisely in Real Estate

Before relying on AI tools for your next deal, take these precautions:

• Always verify price or rent estimates with a real estate agent or appraiser.
• Understand how your data will be used and whether you can opt out.
• Review your credit and background information before applying for loans or leases.
• Look for clear disclosures about how AI makes decisions, and request manual reviews if something seems wrong.
• Watch for patterns that suggest bias or errors.

“Everyone’s at risk if they don’t understand how these tools work,” Huang says. “You’ve got to stay ahead of the curve.”

Why Human Judgment Still Matters

AI is a powerful tool, but it can’t replace experience or personal judgment. Humans are better at catching issues that algorithms miss, reading subtle cues in negotiations, and understanding unique needs. Trust and credibility come from people, not software.

“AI doesn’t give you trust or credibility,” Huang says. “People do.”

The Takeaway

AI is speeding up how commercial real estate deals are found, priced, and closed, but it’s not foolproof. Use AI to your advantage, but always double-check results and rely on experienced professionals for major decisions. The smartest approach combines technology with human insight.

About the Expert: James Huang is Managing Director of Commercial Real Estate at RESAAS Services Inc., a global real estate technology platform. He has over 30 years of experience across banking, finance, and commercial brokerage, and now focuses on integrating AI into real estate transactions worldwide.

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.