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Greenhouse CEO says job seekers are paying $20 to apply for every job on the hiring platform and spamming bosses -- he calls it the AI doom loop | Fortune
Job seekers are exhausted. Tired of shooting résumés into the void and getting ghosted, many have started paying for AI tools that blast their application out to every open role they can find. But according to Greenhouse CEO Daniel Chait, employers are just as miserable -- and he's got a name for the hiring nightmare: an AI doom loop. "This is the first time when really both sides have been unhappy," Chait told Fortune. "The market just isn't working for either side." Job seekers, he says, are "piling more and more job applications into the black hole and not getting any progress." It doesn't matter how many they send -- they "just don't get anywhere." So they've turned to AI tools that make the process less painful. "You can go search on Google, and there are tools that advertise, use AI to automatically apply to every Greenhouse job," the jobs board boss said. "Someone goes and buys that tool, it's like 20 bucks, and now they can just shoot out job applications willy-nilly to as many jobs as they want." On the other side of the inbox, recruiters are drowning. There are currently 175,000 live jobs on Greenhouse's platform -- and on average, for every job ad posted, around 254 job seekers are applying, pushing applications per recruiter up by 412%. "They'll often get hundreds or thousands of applications in just a day or two, and they're not able to keep up with it," Chait said. Worse, because so many of those applications are AI-generated, "they all start to look the same" -- so candidates can no longer tell who is seriously interested from someone who has auto-applied to a thousand jobs overnight. It leaves employers turning to AI just to survive the flood of applications, while candidates who keep getting overlooked respond the only way they know how: applying to even more jobs. "We've called that the AI doom loop," he added. "Everyone's using their own AI to solve their own problem, but it's making the whole system worse," he said. CEOs and even Anne Hathaway are having the same issue: They can't find good candidates because of AI The data backs up how broken things have gotten. More than 1.2 million applications were submitted last year in the U.K. alone for fewer than 17,000 graduate roles. One young man with a master's degree applied to thousands of positions for over six months without a single callback. And it could get even worse: Goodwill's CEO Steve Preston has said the job center is bracing for an influx of jobless young people as AI eats into entry-level roles. For CEO's it means that finding the candidates they want is literally like finding a needle in a haystack. Arvind Jain, the ex-Google engineer behind the $7.2 billion AI startup Glean, explained that his company gets thousands of job applications every single day -- and he still can't find the people he needs, because the best candidates are getting snapped up before he even has time to sift through a fifth of the applications. "Students think it's hard to find jobs, but we think it's hard to find them," he told Fortune. Even the actress Anne Hathaway has run into the same wall. The Odyssey star revealed she was spammed with ChatGPT-written thank you notes after a recent hire. "I just want to warn you: If you're out there thinking that you're getting away with something, there's a chance that you might be revealing yourself," Hathaway said. Greenhouse has a fix for the doom loop -- but networking and handwriting thank you notes help too Chait agrees that the solution isn't for everyone to just stop using AI. The cat is out of the bag, and there are simply too many people applying to too few roles for anyone to go back to doing things the old way. But his company has launched two fixes for now: The first is a feature called "My Dream Job," which lets a job seeker flag just one role a month, across every company on Greenhouse's platform, as their top priority. Because it's scarce, Chait says it forces real intent -- and that intent becomes a signal employers can actually trust. Nearly half a million "dream job" applications have been submitted since launch, and Chait says those candidates get hired at roughly five times the rate of everyone else. The second move: Greenhouse recently acquired an AI voice-interviewing company (Ezra AI Labs), which lets every applicant -- not just a shortlisted few -- get an interview. "Why would I send out automatic thousands of job applications if every single one of them I have to take an interview for?" Chait said. The goal is to kill the incentive to spam in the first place, while also cutting out the résumé-screening stage entirely -- a step Chait says is riddled with bias and adds roughly six days to the hiring process for little real benefit. But for desperate young workers who want to take action in their own hands, there are some ways to stand out among the millions of unemployed people fighting for a job. For one, the extra bit of effort it takes to handwrite a note could be an easy win, especially as one Gen Z hiring manager pointed out that they're few and far between these days. Meanwhile, Netskope CEO Sanjay Beri recently told Fortune that the only reliable way to land a job anymore is to skip the applications entirely and build a relationship with someone on the inside -- because, as he put it, some of the best jobs are "never published" at all. His advice for job seekers who are young, hungry, and child-free is to get out and network at least 2 to 3 times a week: "Who you know, how you get to know them, and building your network will pay off over time."
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Job Seekers Are Using AI to Apply Everywhere, Recruiters Are Using AI to Filter Them -- Greenhouse CEO Calls
Greenhouse CEO Daniel Chait says artificial intelligence is creating a "doom loop" in hiring, as job seekers use AI tools to send applications at scale while overwhelmed recruiters increasingly turn to AI to screen them. Candidates can spend about $20 on tools that automatically apply to Greenhouse jobs, contributing to a surge in applications that recruiters struggle to process, according to a Fortune report published Sunday. Greenhouse currently has about 175,000 live jobs, with an average of 254 applicants per posting, while applications per recruiter have jumped 412%. AI Doom Loop "This is the first time when really both sides have been unhappy," Chait said. "The market just isn't working for either side." As candidates send more AI-generated applications, recruiters use AI to handle the growing volume. Rejected applicants then respond by sending even more automated applications. "We've called that the AI doom loop," Chait said. "Everyone's using their own AI to solve their own problem, but it's making the whole system worse." Chait said recruiters can receive hundreds or thousands of applications within days. With many applications generated using AI, they can also begin to look similar, making it harder for employers to identify candidates who are genuinely interested in a position. Job seekers have already begun experimenting with AI to navigate automated hiring systems. Some candidates are creating multiple resume versions tailored to different skills and keywords, reflecting growing frustration with automated screening. Hiring Squeeze The broader shift is creating an unusual hiring problem: candidates can use AI to apply to far more jobs, while companies can use AI to process far more applicants. That can leave both sides relying increasingly on automation to deal with automation. Greenhouse Fix Greenhouse's "My Dream Job" feature lets candidates mark one job per month as their top choice. Nearly 500,000 such applications have been submitted, with candidates hired at about five times the rate of others. Greenhouse also acquired Ezra AI Labs to offer AI voice interviews and reduce reliance on résumé screening. "Why would I send out automatic thousands of job applications if every single one of them I have to take an interview for?" Chait said. Human Signal As AI applications grow, personal effort could help candidates stand out. Actress Anne Hathaway warned against ChatGPT-written thank-you notes after receiving similar-looking messages during hiring. "If you're out there thinking that you're getting away with something, there's a chance that you might be revealing yourself," Hathaway said. Netskope Inc (NASDAQ:NTSK) CEO Sanjay Beri has also recommended building relationships instead of relying entirely on online applications, noting that some of the best jobs are "never published." "Who you know, how you get to know them, and building your network will pay off over time," Beri said. Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.
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Greenhouse CEO Daniel Chait identifies an AI doom loop in hiring where job seekers use $20 AI tools to mass-apply to jobs while recruiters deploy AI to filter the flood. With 254 applicants per posting and applications per recruiter up 412%, both sides are stuck in a cycle that's making the hiring market worse for everyone.

The hiring market has reached a breaking point where both job seekers and employers are equally frustrated, according to Greenhouse CEO Daniel Chait. Job seekers are spending around $20 on AI tools to mass-apply to positions across the hiring platform, while recruiters deploy their own AI to filter through the resulting deluge. Chait calls this phenomenon an AI doom loop—a cycle where everyone uses automation to solve their individual problem, but collectively makes the entire system worse
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."This is the first time when really both sides have been unhappy," Chait told Fortune. "The market just isn't working for either side"
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. The problem stems from a fundamental imbalance: job seekers using AI can blast applications to thousands of positions overnight, while recruiters using AI to filter them respond by tightening their automated hiring systems, which then prompts even more mass applications.The numbers paint a stark picture of the current hiring ecosystem. Greenhouse currently hosts approximately 175,000 live jobs, with an average of 254 applicants per posting. More alarmingly, applications per recruiter have surged by 412%
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. Recruiters often receive hundreds or thousands of applications within just a day or two of posting a position, creating an impossible workload that forces them to rely on automation.The scale of the problem extends beyond Greenhouse. More than 1.2 million applications were submitted last year in the U.K. alone for fewer than 17,000 graduate roles. One young man with a master's degree applied to thousands of positions over six months without receiving a single callback
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. This résumé ghosting has become so common that job seekers feel they have no choice but to turn to AI tools to mass-apply to every available position.The proliferation of AI-generated applications has created a new challenge for employers: homogeneity. Because so many candidates use similar AI tools to mass-apply, their applications begin to look remarkably alike, making it nearly impossible for recruiters to distinguish genuinely interested candidates from those who have auto-applied to a thousand jobs overnight
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. Even high-profile employers struggle with this issue. Arvind Jain, the ex-Google engineer behind the $7.2 billion AI startup Glean, explained that his company receives thousands of job applications every single day, yet he still can't find the people he needs because the best candidates get snapped up before he can review even a fifth of the applications1
.Actress Anne Hathaway recently experienced this firsthand when she was spammed with ChatGPT-written thank you notes after a recent hire. "If you're out there thinking that you're getting away with something, there's a chance that you might be revealing yourself," Hathaway warned
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.Related Stories
Recognizing that simply asking everyone to stop using AI isn't realistic, Daniel Chait and Greenhouse have launched two features designed to restore signal to the hiring process. The first is the My Dream Job feature, which allows job seekers to flag just one role per month across every company on Greenhouse's platform as their top priority. Because this designation is scarce—limited to one per month—it forces genuine intent and creates a signal that employers can actually trust. Nearly 500,000 "dream job" applications have been submitted since launch, and candidates using this feature get hired at roughly five times the rate of everyone else
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.The second solution involves Greenhouse's recent acquisition of Ezra AI Labs, which enables AI voice interviews for every applicant—not just a shortlisted few. "Why would I send out automatic thousands of job applications if every single one of them I have to take an interview for?" Chait asked
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. The goal is to eliminate the incentive to spam applications in the first place while cutting out the résumé-screening stage entirely—a step Chait says is riddled with résumé-screening bias and adds roughly six days to the hiring process for little real benefit.As automated hiring systems become more prevalent, experts suggest that building human networks may be the most effective way to stand out. Netskope CEO Sanjay Beri has recommended that candidates focus on building relationships instead of relying entirely on online applications, noting that some of the best jobs are "never published." "Who you know, how you get to know them, and building your network will pay off over time," Beri said
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. This advice becomes particularly relevant as Goodwill's CEO Steve Preston has warned that job centers are bracing for an influx of jobless young people as AI eats into entry-level roles1
. The short-term implications are clear: candidates who continue to rely solely on AI tools to mass-apply will find themselves competing with millions of identical applications, while those who invest in personal connections and demonstrate genuine intent may find doors opening faster. Long-term, the hiring market may need to fundamentally restructure how it matches talent with opportunity, moving away from volume-based screening toward more meaningful signals of fit and interest.Summarized by
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