The rise of AI in CRE - And what it means for every skilled profession - A broker & appraiser weighs in - by Bryan Plourde

This may seem self-serving, and I’ll be the first to admit it. But unlike some of the artificial intelligence tools now reshaping our industry, I am fully aware of my own bias. So, hear me out. The rise of AI in commercial real estate is not a distant threat or a speculative headline. It is already here, quietly absorbing the administrative weight that has long defined our days: lease abstractions, comp searches, zoning lookups, financial modeling, market reports, and the endless email threads that accompany every transaction. These are tasks that once required hours of trained labor, and machines are now performing them in seconds. What AI is particularly good at is reducing the friction between the origin of an idea and its execution. The gap between thinking something and doing it, especially on the administrative side, is collapsing in ways that should feel liberating to anyone who has spent a career buried in the procedural. For brokers and appraisers who built their value around access to information, this is a legitimate reckoning. But it is also, if we are honest with ourselves, an opportunity to shed the work we were never truly built for and return to the work that only we can do. What AI cannot replicate is the texture of local market knowledge accumulated through years of showing space, shaking hands, and sitting across the table from people whose motivations rarely appear in a spreadsheet. A broker who has worked a particular submarket for fifteen years carries in their head a living map of who owns what, who is quietly distressed, which owners have room to move and which are fixed in their terms, and which relationships need to be carefully managed before a letter of intent is ever drafted. This is not data. It is knowledge shaped by repetition, failure, and hard-won trust. No algorithm trained on public records and transaction histories can replicate the phone call a seasoned broker makes at seven in the morning to a contact who will say things off the record that never make it into any database.

Consider the deals that never quite appear the way they actually happened. I have watched brokers, good ones and respected ones, quietly absorb an entire lease transaction just to keep a sale from falling apart. The economics of the larger deal demanded it, and so they structured a lease arrangement between the parties, negotiated the terms, papered it, and walked away without a commission because the alternative was watching years of work collapse at the finish line. That concession, that act of professional judgment and sacrifice, shows up nowhere in the sales data. The recorded price looks clean. The cap rate appears rational. But the true story, the one that actually explains why that buyer stayed at the table, lives only in the memory of the people who were in the room. Appraisers face a parallel challenge, one that strikes at the very methodology their profession is built upon. The market data an appraiser relies on is only as good as the facts behind it, and primary research is necessary to confirm those facts. I have seen appraisers go to extraordinary lengths to uncover the truth behind a transaction, contacting buyers, sellers, brokers, and attorneys not simply to confirm a sale price, but to listen carefully to how people respond. A hesitation. An overly rehearsed answer. A broker who redirects too quickly. These are signals that something beyond typical market motivation may be at play: a divorce, a foreclosure avoidance, a 1031 exchange with a hard deadline, an abutter purchase, a family transfer dressed as an arm’s length sale. The ability to read those signals, to ask the right follow-up question, to judge the credibility of a market participant based on how they speak rather than just what they say, is a craft that takes years to develop and cannot be reduced to a training dataset. To the appraiser, the selection and confirmation of truly comparable data for analyses is paramount for credible results.

The deeper truth is that the abundance of AI-generated information will not make our jobs easier so much as it will raise the stakes of getting things wrong. When every market participant has access to the same secondary data, the same comp sets, and the same AI-drafted offering memoranda, the differentiator will not be who has the most data but who best understands its limitations. Verification, once treated as background work, becomes the central professional act. The broker or appraiser who can look at a clean set of numbers and recognize that something does not add up, and then do the work to find out why, will be more valuable in an AI-saturated market than they ever were in one defined by information scarcity. The noise will be louder, the signal harder to find, and finding it will require exactly the kind of professional human judgment that cannot be simply downloaded. There is genuine reason for optimism here, even for those of us who built careers on capabilities that machines are beginning to replicate. If sixty to eighty percent of what we do can be automated, then what remains is not the lesser portion of our work. It is the best of it. The negotiation, the verification, the relationship, the experienced judgment call made at the edge of incomplete information: these are the things that drew many of us to this profession in the first place. Justin Gohn, MAI, a well-respected appraiser, has framed this shift in terms worth holding onto: the experienced professional, he argues, becomes an orchestrator and a delegator, directing AI tools with the same authority and intentionality that a seasoned partner brings to managing a team. In other words, AI will not make experienced brokers and appraisers obsolete. It will, if we allow it, strip away the noise and leave us doing the work we were always meant to do. 

That knowledge, gathered over years and taught from mentor to apprentice and refined through the friction of real transactions with real consequences, is not a relic of a pre-digital era. It is the foundation that gives AI-generated information any meaning at all.

This is not a story unique to commercial real estate. The same reckoning is playing out in every field where deep expertise meets the new capacity of machines to process information at scale. The engineer who has spent decades understanding how materials actually behave in the field, not just in simulation, is not replaceable by a structural analysis algorithm, even a very good one. The attorney who reads a counterparty’s posture across the table and knows when a clause is a dealbreaker versus a negotiating position is doing something no contract-drafting AI can replicate. The scientist who recognizes the anomaly in data that everyone else dismissed, and has the intuition to follow it, is exercising a form of judgment built on years of disciplined failure. The accountant who understands not just the numbers but the business behind them, who knows which line items tell the real story and which are artifacts of convention, is providing a service that goes well beyond what any automated audit tool can offer. The marketing strategist who understands human motivation at the level of culture, community, and timing brings something to a campaign that no generative tool can supply from first principles. In every skilled profession, the pattern is the same: AI absorbs the retrievable, the repeatable, and the procedural. What it cannot absorb is the twenty to forty percent that required a human being to be present, to have made mistakes, to have developed instincts through exposure to outcomes, and to exercise judgment in conditions where the stakes are real.

I will close with a small confession. In my undergrad days I was a devoted philosophy and economics major who could turn out a term paper on short notice and took no small amount of pride in it. The irony, then, is not lost on me: AI assisted with the syntax and structure of this very article. But the inputs, the ideas, the convictions, and the observations gathered from years in the field, along with the strategy, the editorial judgment, the professional context, and the conclusions that give this piece its meaning, those belong to me, and to the years of work that made them possible. Which, come to think of it, is precisely the point. In every profession worth practicing, AI is a powerful tool in skilled hands. It is the hands that matter.

Bryan Plourde, MAI is a broker with The Dunham Group, and a certified general commercial real estate appraiser with Maine Valuation Company.