In July, software engineer Julian Joseph became the latest victim of the tech industry’s sweeping job cuts. Facing his second layoff in two years, he dreaded spending another couple months hunched over his laptop filling out repetitive job applications and blasting them into the void.
Joseph specializes in user interface automation and figured someone must have roboticized the unpleasant task of applying for jobs. Casting about online, he came upon a company called LazyApply. It offers an AI-powered service called Job GPT that promises to automatically apply to thousands of jobs “in a single click.” All he had to fill in was some basic information about his skills, experience, and desired position.
After Joseph paid $250 for a lifetime unlimited plan and installed LazyApply’s Chrome extension, he watched the bot zip through applications on his behalf on sites like LinkedIn and Indeed, targeting jobs that matched his criteria. Thirsting for efficiency, he installed the app on his boyfriend’s laptop too, and he went to bed with two computers furiously churning through reams of applications. By morning, the bot had applied to close to 1,000 jobs on his behalf.
The tool wasn’t perfect. It appeared to guess the answers to questions on some applications, with sometimes confused results. But in a brute force kind of way, it worked. After LazyApply completed applications for some 5,000 jobs, Joseph says he landed around 20 interviews, a hit rate of about a half percent. Compared to the 20 interviews he’d landed after manually applying to 200 to 300 jobs, the success rate was dismal. But given the time Job GPT saved, Joseph felt it was worth the investment. LazyApply didn’t respond to a question about how the service works.
Many job seekers will understand the allure of automating applications. Slogging through different applicant tracking systems to reenter the same information, knowing that you are likely to be ghosted or auto-rejected by an algorithm, is a grind, and technology hasn’t made the process quicker. The average time to make a new hire reached an all-time high of 44 days this year, according to a study across 25 countries by the talent solutions company AMS and the Josh Bersin Company, an HR advisory firm. “The fact that this tool exists suggests that something is broken in the process,” Joseph says. “I see it as taking back some of the power that’s been ceded to the companies over the years.”
Recruiters are less enamored with the idea of bots besieging their application portals. When Christine Nichlos, CEO of the talent acquisition company People Science, told her recruiting staff about the tools, the news raised a collective groan. She and some others see the use of AI as a sign that a candidate isn’t serious about a job. “It’s like asking out every woman in the bar, regardless of who they are,” says a recruiting manager at a Fortune 500 company who asked to remain anonymous because he wasn’t authorized to speak on behalf of his employer.
Other recruiters are less concerned. “I don’t really care how the résumé gets to me as long as the person is a valid person,” says Emi Dawson, who runs the tech recruiting firm NeedleFinder Recruiting. For years, some candidates have outsourced their applications to inexpensive workers in other countries. She estimates that 95 percent of the applications she gets come from totally unqualified candidates, but she says her applicant tracking software filters most of them out—perhaps the fate of some of the 99.5 percent of Joseph’s LazyApply applications that vanished into the ether.
LazyApply has plenty of competition, some of which involve humans to pick up any slack. A company called Sonara charges up to $80 per month to auto-complete as many as 420 applications and recommends jobs from a database compiled through partnerships with applicant tracking firms and companies that scrape job listings. Users can teach the algorithm about their preferences by liking and unliking jobs, and it offers to run jobs past the user before firing up its automated application filler. Human staff take over where the AI falls short, for instance, on certain free-text answers.
For $39 a month, a service called Massive will fill out up to 50 automated applications per week and has humans review every application for accuracy. Some companies offer additional services, like AI-generated cover letters and messages to hiring managers. LazyApply will even help users quit a job, by automating their resignation letter.
Many of these services hinge on the notion that job hunting is a numbers game. Dawson allows that for early career candidates, there’s some truth to the idea. “But if you’re an established professional, it’s quality over quantity,” she says. “The number one way to find a job is through referrals,” says Nichlos, whose firm calculates that about a third of hires are made this way. “That hasn’t changed in a really long time.”
When Sonara founder Victor Schwartz was applying for jobs during his senior year studying computer science and machine learning at Duke University in 2019, he heard similar advice: Network, network, network. He found it puzzling. “What do you mean?” he would respond. “I’m 22 and coming out of school.” Without a professional network to tap, Schwartz would spend hours applying through LinkedIn or Indeed, only to get ghosted, sometimes after multiple interview rounds. “It felt like this world was conspiring against me,” he says.
Schwartz began working on Sonara in 2019, reasoning that even if networking is effective, most people won’t do it “because it’s terrifying.” Initially, he hired a team in Brazil to manually complete applications. Sonara launched its AI-powered service in March and currently has 5,000 users, Schwartz says. He’s working on a feature that would automatically tailor résumés to individual job descriptions before submission.
Auto-apply services tend not to disclose that a bot did the work in lieu of a person, but recruiters can spot telltale signs. An application that rolls in within seconds of a job post going up is a giveaway, as is a candidate not knowing which jobs they’ve applied to. “One of the worst things I can hear from somebody who just sent me their résumé is that they had no idea they just did that,” says Marcus Ronaldi, who owns Ronaldi Recruiting and specializes in accounting and chemical and mechanical engineering roles. After recommending a candidate to a company, he’ll sometimes hear back that they already applied, meaning he can’t represent them—but he’ll find the candidate didn’t know it themself, because they outsourced the process to a bot.
Dawson recalls one candidate who she guessed was using AI because they didn’t know how many jobs they’d applied to and struggled to respond when she contacted them to say her client was interested. “The candidate was overwhelmed by how many things they had going on at one time,” she says, “It’s OK to apply for many jobs, but it’s also really important to pay close attention to what’s in front of you.”
Indiscriminately spraying applications all over the internet could have other implications—especially if the advent of services like LazyApply prompt the companies behind applicant management software to respond. “Some of these tools are really sophisticated. They could identify you as a spammer,” says Josh Bersin, CEO of the eponymous HR advisory firm. Nichlos thinks AI could better help both job hunters and recruiters if it identified a small pool of the most suitable roles for a person to apply for—or a recruiter to offer up. That might work best if AI tools focused on one specialty. “We need to get more myopic,” she says.
Dan Vykhopen’s company Massive is working on the matching problem. “Filling out applications is easy” for AI, he says. “Matching is hard.” Massive aggregates information about a company, such as its culture and leaders, from sources like startup databases Crunchbase and Harmonic and job review site Glassdoor. Job seekers can use that data to hone their job search, using criteria such as the quality of the benefits, the experience of the founders, or the success of the investors. Right now, Massive focuses on tech jobs because the industry is easier to map, says Vykhopen, but he hopes to expand in the future.
Gabrielle Judge, a TikTok influencer who coined the term “lazy girl job” to describe the ideal of a reasonably compensated but undemanding job, created an online course advising job seekers on how to leverage AI. (She’s a paid influencer for Sonara.) She recommends that applicants use AI as one weapon in a diverse arsenal that includes networking and conventional web search. “If you’re only using AI as your job-seeking strategy, you could be missing out on some really cool dream roles you might find if you did some manual searching,” she says.
Julian Joseph agrees. He says having LazyApply handle the grunt work frees him up to network and pursue other strategies without having to worry that he’s missing out on the latest job ads. Yet not all the interviews the tool landed him were great matches. He was searching for “DevOps” roles involving development and deployment of software for Salesforce’s cloud platform, but LazyApply sometimes applied to sales jobs that involved simply using Salesforce applications. Other times, the bot found jobs that turned out to be better than advertised. One role, for instance, didn’t advertise itself as remote, his preference, but he learned during the interview that remote work was an option.
“The tool helped me to find jobs that I might have skipped over,” Joseph says. Even interviewing for a bad match felt like a better use of his time than the grind of filling out applications. “Even if it’s not a perfect fit, I’m getting better at interviewing. And I’m learning more about what I want.” He’s received an offer for a contract job he found through LazyApply, and he also landed interviews at Apple and the White House. He found those last two opportunities through his own connections.