About half of Marquette University’s real estate class of 2026 graduated this spring without a job lined up.
A year earlier, about 55% had offers by graduation. This year’s class didn’t reach 80% placement until three months later, and it is still short of the 90% the 2025 class hit within six months — even though the program works with every student individually until they land a job.
Peer programs are reporting similar numbers, said Andrew Hunt, executive director of Marquette’s Vieth Institute for Real Estate Leadership.
“They’re all still getting jobs, but they’re not getting jobs as early as they used to,” Hunt said. “And they have to work way harder to get them.”
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The grunt work that has long taught junior analysts the business, like crunching numbers, building models and summarizing deals, is exactly the work artificial intelligence is getting good at, and that is stirring anxiety up and down real estate’s time-honored career ladder.
Wall Street has already flinched. In February, the AI scare trade wiped billions off brokerage stocks, driven by fears that AI could replace the human expertise CRE runs on.
Now the question is landing on the industry’s newest workers: If a machine can do the work that used to train them, what is the first job for?
The answer is still being written, but the early drafts are sobering. Entry-level openings have become scarcer, the competition for them is fiercer, and employers are now asking for skills that didn’t appear in job postings two years ago. The schools that feed the industry are scrambling to keep up.
The squeeze isn’t unique to real estate. Employment for 22-to-25-year-olds in the jobs most exposed to AI has fallen about 13% relative to their less exposed peers, according to Stanford’s Digital Economy Lab. In CRE, data from the SelectLeaders job board, which Bisnow owns, tells a similar story.
Postings open to candidates with two years of experience or less made up 3.1% of listings in the 15 months through September, down from 5.1% in the 15 months before. That is a nearly 40% drop in the share of jobs aimed at newcomers.
Those who find an opening have plenty of competition. Entry-level postings drew an average of 55.7 applications each this year, more than four times the roughly 12 a vice president or director role attracts, and that counts only applications submitted through SelectLeaders.
Hunt blames part of the slowdown in his students’ hiring on AI and a glut of candidates, which lets employers be picky and lean on who they already know.
“The relationship side has like 10x’d,” he said.
One brokerage told him it had posted a job, but “honestly, we haven’t even looked at any of the applicants.”
Pay, meanwhile, is stuck. The median entry-level salary band has hovered between $87,500 and $95K every year since 2024.
What is moving is the ask. About 1 in 4 entry-level postings on SelectLeaders this year mention AI, up from roughly 1 in 11 in 2025 and none in a sample of 2024 listings. The sample is small, just seven of 26 postings this year, but the arrow points one way.
One Los Angeles investment firm’s 2024 analyst posting wanted a strong GPA, advanced Excel skills and some familiarity with Argus. When the firm reposted the job this year, the listing was nearly the same word for word, with one addition: The analyst would need strong proficiency with AI tools to automate data extraction, pipeline prep and deal summaries.
Hunt hasn’t seen that demand reach Marquette yet.
“I have not had anyone come to us and say, ‘Well, we only want to hire someone if they have AI skills,’” he said.
However, Hunt said, “They are all AI-curious. All of them, every single one.”
Most firms are still figuring out AI inside their own walls, he said, and they are wary of handing a junior hire what he called “the most powerful tool that our company has ever seen.” The early adopters are writing AI into postings, and the rest will follow once they see a return, he predicted.
At Marquette, Hunt’s answer is fundamentals first, AI second. He calls the argument that AI makes students think less “a lazy take” and puts the burden on professors to learn the tools well enough to teach them.
“There is no company out there that is going to hire you just to do AI and not understand what a cap rate is,” he said. “You have to know that stuff.”
In his financial modeling class, students start with a pro forma on the back of a napkin, then build a full Excel model by hand, together, in class. Only then does AI enter the room, including examples where it got the answer wrong. Students are graded on catching the problems in an AI-built model, not on producing one.
Through Marquette’s AI in Real Estate Lab, students tackle real problems for CRE firms. One built a tenant intelligence platform that replaced a brokerage team’s old system, plus an AI tool that auto-builds the team’s availability decks in PowerPoint, Hunt said.
For students and parents weighing tuition, Hunt’s pitch is that the human side of the business is becoming more valuable, not less.
“If you want to sit on your couch and just have ChatGPT teach you all this stuff, absolutely do it for $20 a month. It’s going to be a great tutor,” he said. “But if you want to be a leader in this industry, you need to come to a place like this that’s going to put you in a position to be networking with other leaders.”
The human element, he added, “is going to only become more and more important, and that’s why you need us.”
Almost none of the entry-level postings ask for coding skills like Python, and Hunt said students don’t need them. They need to be able to describe what they want and let AI write the code, a practice known as vibe coding.
“If you have charisma and you can vibe code, you can take over the world,” he said.
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