Three years ago, Andrew Stockwell, then Head of People at Vendr, a software procurement company, had a hiring routine honed to near perfection. His process typically involved posting a job listing, patiently waiting a few days, and then meticulously reviewing a few dozen applications, sometimes up to 100 if fortune favored him. Recruiters would supplement this pool by identifying additional potential candidates. Stockwell’s role was to sift through resumes, conduct interviews, and present the most promising individuals to hiring managers. “It was really about finding that great talent, sussing out that talent, speaking with that talent, and identifying the best possible people,” Stockwell recounted to WIRED. This methodical approach, focused on quality over sheer quantity, was the industry standard for effective talent acquisition.
However, over the past year to eighteen months, Stockwell observed a seismic shift in the landscape of recruitment. The initial steps of the hiring process remained familiar, but the outcome was drastically altered. Instead of a manageable handful of applications, Stockwell found himself inundated. Within a day or two of posting a role, he was no longer reviewing dozens, but hundreds, sometimes even exceeding a thousand applications. This surge presented a new, daunting challenge: a significant portion of these submissions were "total bogus," as Stockwell described, often from fake candidates or seemingly generated by artificial intelligence. These AI-crafted applications, while sometimes sophisticated, often stretched the truth and blurred the lines between genuine candidates, making it exceedingly difficult to differentiate individuals. The sheer volume became overwhelming, forcing Stockwell to deploy his highly paid and skilled talent acquisition professionals solely to sift through mountains of applications all day long.
Stockwell’s experience is not an isolated incident. He is one of many recruitment professionals who believe the fundamental mechanics of job searching have been irrevocably broken. The advent of readily accessible AI tools has transformed job hunting into something akin to online shopping. In mere seconds, AI can generate tailored resumes and cover letters, meticulously crafted to match specific job descriptions. Browser extensions can automate the application process, eliminating the need for human intervention. Platforms like LinkedIn, once a powerful networking tool, now inundate users with dozens of job recommendations daily, many featuring a "apply with just a few clicks" option, further streamlining an already frictionless process.
Ophir Samson, Head of Voice AI for Greenhouse, a prominent recruiting platform, echoed this sentiment. "A year ago, every recruiter would tell me: We want to make it as easy as possible to apply for jobs," Samson told WIRED, referencing the industry’s drive to offer candidates a "seamless experience." Samson, who joined Greenhouse earlier this year following the acquisition of his startup that specialized in AI-powered job interviews, elaborated on the unintended consequences. "What they got was 2,000 applicants in 24 hours for a job. That is a shitty experience for everyone."
This unprecedented influx of applications has created a paradoxical situation where genuine, qualified applicants struggle to stand out amidst the noise, while less scrupulous or poorly matched candidates can slip through the cracks. Recruiters, Samson explains, are now burdened with the "tortuous task of judging thousands of candidates, every single day." Instead of dedicating time to proactively search for ideal candidates on platforms like LinkedIn, they find themselves entrenched in applicant tracking systems, meticulously tweaking filters in a desperate attempt to identify which applications warrant even a brief skim.
The irony of the situation is that the initial impetus behind these simplified application processes was to improve efficiency and broaden the reach for employers. For years, recruiters actively sought to reduce the friction in applying for jobs. They posted on numerous job boards and LinkedIn, embraced features like LinkedIn’s "Easy Apply," and promised candidates a "one-click" application experience. This push for simplification intensified post-pandemic as companies grappled with widespread labor shortages and a highly competitive talent market.
The Post-Pandemic Job Market Shift
Jane Curran, Chief Transformation Officer at the real estate giant JLL, recalled the frenetic job market of the pandemic era. "Everyone was job hopping, because you literally could have three offers in an afternoon," she told WIRED. "Now, it is the polar opposite." This stark reversal is supported by data from the Bureau of Labor Statistics. Job openings in the United States peaked at a record 12.3 million in March 2022, reflecting a period of intense demand for labor. However, this was followed by two years of decline, with openings hovering around 7 million by mid-2024, a significant contraction from the peak.
While the number of available positions decreased, the barriers to entry for job applicants continued to erode, largely driven by the rapid mainstream adoption of artificial intelligence following the public release of ChatGPT in late 2022. AI tools empower applicants to rapidly generate and refine resumes, and to track new job postings almost instantaneously. Companies such as JobAssist, Sonara, and Ladder’s Apply4Me have emerged, explicitly promising applicants that their AI-powered technology can handle the laborious task of applying for jobs, enabling them to submit "10x as many applications with less effort than one manual application." The practical implication is that an individual could, with sufficient automation, apply for dozens of jobs in a single day.
The Avalanche of Applications and Its Consequences
This frictionless application model has directly contributed to the ballooning candidate pools and the subsequent laborious nature of hiring processes. LinkedIn has reported a 46 percent increase in submissions per applicant on its platform compared to February 2020. Since the widespread adoption of ChatGPT, applications on the platform have seen a 22 percent surge. The sheer volume of these applications has become so pronounced that LinkedIn has begun implementing measures to curb automated and low-quality submissions. This month, the platform is rolling out a new feature designed to inform applicants who appear to be underqualified that they may not be a suitable fit for a role, while simultaneously suggesting alternative positions.
Tessa White, a former HR executive and now a prominent voice on the job market through her extensive TikTok following, observes the current predicament with concern. "We’re currently in a place where employers are complaining that they can’t find good people, and people are complaining that they can’t find jobs," White told WIRED. White, who left corporate America in 2018 after two decades in HR, has built a following of over 800,000 on TikTok by sharing insights and advice on the job market. She attributes the current untenable situation to the relentless pursuit of speed and ease by recruiters. "Every time we seem to strive for efficiency, we seem to give up quality," she stated.
While an overwhelming number of resumes might be beneficial for certain roles, such as skilled trades where demand consistently outstrips supply, the scenario is far more challenging for the typical white-collar knowledge worker. JLL’s Curran notes that in these sectors, "there is not enough churn, not enough jobs coming into the market." Consequently, recruiters in these fields are faced with a barrage of applications for every new role they post.
AI as a Double-Edged Sword: Solutions and Lingering Problems
In response to this overwhelming influx, many recruiters are turning to AI tools themselves, hoping to transform the sea of applications into something more manageable. While automated applicant tracking systems (ATS) have been a staple in screening resumes for over a decade, many companies are now deploying AI agents to conduct initial candidate interviews.
"We frequently hear from recruiters: They have 1,000 applications, but they know that only 30 of them are serious," Greenhouse’s Samson explained. He believes that AI-powered interviews can effectively differentiate between serious and unserious candidates, offering recruiters valuable context beyond what a resume alone can provide.
Samson emphasizes that these AI interviews are not intended to create artificial friction for its own sake, but rather to serve the practical purpose of weeding out bots and candidates who are not genuinely invested in the application process. Curran anticipates that some companies will implement "knock-out questions" designed to immediately filter out candidates who do not meet strict criteria. Others may opt to incorporate skills testing earlier in the application pipeline.
However, White remains skeptical that these measures fully address the underlying problem. She argues that the ease of submitting applications has rendered the initial stages of the hiring process largely ineffective. "Employers are having such a hard time hiring people with the current antiquated process," White asserted. "Even AI and applicant tracking systems, which sound so high-tech, are an antiquated way to look at people and skill sets." She contends that current AI capabilities are insufficient to accurately assess an individual’s true potential.
"I definitely think recruiting and the way we do it is due for a massive overhaul," White concluded. "And I don’t even know that I have the right answers."
The Return to Human Connection and its Limitations
The overwhelming volume of applications has inadvertently led to an increased reliance on referrals and internal hires. While these human-to-human connections have always been a crucial component of recruitment, some now view them as the only viable method to circumvent the current glut of applications. Stockwell, however, expresses concern that this trend may inadvertently favor candidates whose backgrounds align with those of existing employees, potentially hindering the development of a diverse workforce. "The whole thing is a big mess," he lamented.
Stockwell is now experiencing the challenges of this broken system from the other side of the application portal. In February, he departed Vendr and is currently navigating the job market himself. He approaches his search with the dedication of a full-time job, "pounding the pavement" and actively attending in-person networking events. He understands that without a personal connection, the likelihood of securing an interview is virtually nil. When he submits applications online, he estimates that it leads to a phone interview less than 2 percent of the time.
"I’m biased, of course, about my own capabilities," Stockwell stated. "But companies are missing out on fantastic talent." His personal experience underscores the broader implications of the current hiring landscape: a system designed for efficiency has, in practice, created significant barriers to entry for both employers and highly qualified candidates, leading to a fundamental breakdown in the talent acquisition process. The future of recruiting may lie in finding a delicate balance, reintroducing meaningful friction where necessary to ensure quality, while still leveraging technology to streamline the identification of genuine talent.
