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LinkedIn's CEO blames a 30% rise in applications for making good hires harder to spot
LinkedIn chief executive Dan Shapero says job seekers send 30% more applications than before the pandemic, as US openings fell to 7.08 million in August. Hiring is also close to a ten-year low, so the figures cannot yet separate an AI-polished applicant pool from plain weaker demand.
The Investor · Invest desk
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What happened
- LinkedIn's Dan Shapero says recruiters now have to dig through hundreds or thousands of applicants, which makes the right hire harder to find.
- The number of Americans hired each month, leaving the pandemic years aside, is nearing a ten-year low.
- Around 63% of US job seekers have been interviewed by AI, Greenhouse reported this year, up 13% from six months earlier.
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Why it matters
- contradiction Simplify's data implies a rise about three and a half times the one Shapero cites, so how big the flood looks depends on whose sample is used, and graduates appear to account for the steepest part.
- constraint With hires near a ten-year low, weak demand and AI-polished applications produce the same symptoms, so employers cannot yet pin slow hiring on applicant tools.
- decision Because LinkedIn's assistant narrows pools without rejecting anyone, employers still pay a human to make the final cut, and the tool is worth what it saves of that time.
- cost Greenhouse's Tipton puts the heaviest cost on candidates, who now face AI screens and AI interviewers without being told the process has changed.
Simplify's numbers show a much bigger flood than Shapero's. The platform's data, shared with Fortune, put the average job hunter at 45 applications a month in May of last year against 22 across 2024 [6]. That is a rise of about 105% [1], roughly three and a half times the 30% LinkedIn's chief cites [2], and his figure is measured against a pre-pandemic baseline [3]. Fortune's account does not say whether the 30% is per applicant or in total. Simplify's breakdown is by student degree, with master's students sending 32 to 60 applications a month and bachelor's students 15 to 38 [7].
Shapero's explanation is that candidates use AI to "get a leg up" by applying widely and to "look great to potential employers" [15], so the pool grows and starts to look alike. A second reading puts the cause in demand. Openings hit a five-month low of 7.08 million in August [2], and monthly hiring outside the pandemic years is close to a ten-year low [4]. When each application is worth less, candidates send more. A third reading keeps the flood mostly among graduates, where Simplify's steepest figures sit [7], and away from the typical employer's inbox.
In my view the second reading explains most of it. A 30% rise over several years [3] is modest for a market hiring at close to a decade low [4], and applying more when fewer postings turn into hires is what a rational candidate does. The strongest case against that view is Shapero's own, and it is about how alike the applications look. "It creates a challenge where we are just living in a world where there is a sea of applicants coming in our direction that look pretty similar," he said at LinkedIn's Talent Connect conference [12]. Nearly two-thirds of job seekers use AI for resumes and cover letters [8]. Documents tailored with the same tools give a screener less to tell candidates apart at any volume.
Employers have answered with software. Around 99% of hiring managers told Insight Global they use AI in hiring [9], and about 63% of US job seekers have been interviewed by AI, according to Greenhouse [11]. LinkedIn has its own AI Hiring Assistant to filter incoming applications [10]. The executive describing the flood also runs a company with a product built to sort it. Shapero said the assistant does not automatically reject anyone [10]. LinkedIn narrows the pool and leaves the final cut, along with the recruiter hours it takes, to the employer.
Sharawn Tipton, chief people officer at Greenhouse, told Fortune who she thinks pays. "Recruiters are inundated, and they're worried about being replaced," she said [13]. "The cost of all of this falls hardest on candidates" [14].
The weak-demand reading fails if applications stay near 30% above the pre-pandemic level [3] once openings climb back from 7.08 million [2]. If they fall back as hiring recovers from near a ten-year low [4], the screening problem was mostly a hiring slump.
What to watch
- A LinkedIn breakdown of its 30% figure by applicant, showing whether each person applies more or more people are applying.
- Greenhouse's next reading on AI-conducted interviews, after 63% of US job seekers reported having one.
- Any move to let LinkedIn's Hiring Assistant reject candidates automatically, which would hand the final cut from recruiters to software.