AI Won’t Kill Office Brokerage. But It Will Force Some Hard Questions.
The information problem inside office brokerage
AI is forcing office brokerage to confront a question that has been building for years, where does advisory value come from when market information becomes easier to access, compare, and verify? In this guest contribution, Zoe Ellis-Moore explores why the best brokers will remain valuable, why weak data creates friction in flex, and why a more transparent market may ultimately benefit clients, operators, and advisors.
In February 2026, Wall Street wiped nearly $12 billion from the market values of the world’s biggest real estate brokerages in two trading days.
CBRE had just reported strong revenue growth.
JLL was profitable.
Nobody was having a bad quarter.
Investors were pricing in something else entirely, the possibility that AI will eventually erode the value of human expertise in a business that has always run on knowing things others do not 1.
The reaction was covered widely across the property press.
AI disruption fears hit CBRE, JLL, Cushman & Wakefield, Colliers and Newmark, while the conversation spread quickly into Europe, affecting firms including Savills, IWG, British Land and Landsec.
The firms pushed back, share prices recovered somewhat, and the conversation has kept going ever since, with senior figures across the industry now openly debating what AI actually means for how deals get done.2
Having spent 22 years in commercial property, and the last 7 in flex offices, I find myself watching this debate with interest. The question of whether AI threatens brokerage is real and worth taking seriously. What tends to get missed is the deeper structural problem that AI is now making impossible to ignore.
What Brokers Actually Sold
For a long time, a broker’s value was tied to knowing things.
Which buildings had availability before the listing went public?
Which landlords would negotiate on price?
Who was about to sign a big lease two streets away?
That information advantage was real,
it was hard to replicate, and clients paid for it.
That is changing.
Data platforms now surface buildings in seconds.
AI can pull comparable rents, amenities and lease terms without a phone call. CBRE has said it expects to cut research costs by around 25% through AI adoption. That says less about crisis and more about the fact that a meaningful part of what brokerages have always done can now be automated.3
The brokers I respect are not especially alarmed by this.
The work they find most interesting and most valuable to clients was never really about the database query.
It was the judgment call.
The read on whether a landlord will flex on fit-out.
The understanding of how much space a company actually needs versus how much it thinks it needs.
That part is harder to automate, and it matters more.
Where Brokers Fit Into This
Good brokers would benefit from better data as much as anyone.
When the baseline information is clearer and independently verified, the advisory conversation shifts. Rather than unpicking what a provider actually offers beneath the marketing language, a broker can focus on whether a space genuinely fits a client’s culture, how it handles headcount growth, and what the renewal terms look like in practice.
JLL CEO Christian Ulbrich put it well in a widely covered industry discussion when he said:
“The train has left the station, and it is going at Japanese speed levels of train, very, very fast.”4
The brokers who will do well over the next decade are those who apply the same logic to occupier advice. The market will get more transparent. AI will continue to compress the cost of research, and that will keep raising the question of what advisors are actually adding.
The answer, for the good ones, is judgment applied to better information.
The ones who relied on controlling access to the information in the first place should be paying attention right now.
Flex Has Its Own Version of This Problem
The flexible workspace sector is a useful case study because the transparency gap is already visible and is causing friction.
London alone has hundreds of flex buildings run by dozens of operators, a market that has grown significantly over the past decade and continues to expand.
Yet the process of choosing a workplace still produces a lot of friction.
You find the same words everywhere:
Plug and Play
Premium
Grade A
Community
Flexible terms
None of it is technically false, and very little of it helps anyone make a decision.
The commission model that underpins most flex brokerage is not inherently the problem. Good brokers add real value, particularly on complex requirements.
The issue lies further back.
AI will surface more of this information faster, but there is a lot of AI slop even within paid-for data services.
The data underneath still needs to be trustworthy.
The next phase of the flex market will need more independent verification, more consistent inspection criteria, and more genuine user feedback.
Operator-supplied marketing language has a role, but it cannot be the only basis on which companies, brokers, or AI-powered search tools compare workplaces.
That is the problem Office Tier List is focused on.
Improving the integrity of the underlying data so that whatever comes next, whether a broker recommendation, an AI-powered shortlist, or a company doing its own research, starts from something more reliable.
A More Honest Market
Commercial real estate runs on relationships and probably always will.
What AI is changing, gradually and then quite quickly, is the quality of the information those relationships are built on.
That creates real pressure in parts of the market that have historically relied on opacity. It creates an opportunity for operators with genuine quality to demonstrate it, and for advisors who can work with verified data rather than around the lack of it.
AI will not remove the need for brokers, operators, or advisors.
But it will make weak claims easier to expose, weak data harder to hide, and weak advisory models harder to defend.
That is not the end of brokerage.
It is the beginning of a more accountable market.
Zoe Ellis-Moore is CEO and Founder of Spaces to Places, a research and marketing consultancy for the flexible workspace sector, and Founder of Office Tier List, an independent verification platform for flexible offices in London.