Recruiters are 'drinking through a fire hose' of job applications, experts say—AI is partially to blame (www.cnbc.com)

Recruiters and job seekers are wrestling with a dramatic rise in application volume that’s straining hiring systems and slowing processes. LinkedIn says applications jumped more than 45% year-over-year—nearly 9,500 submitted every minute—and individual roles can attract 300–500 applications in days (some exceed 1,000). In-house recruiters report spending 30 seconds to two minutes per resume while many U.S. HR pros spend 3–5 hours daily on applications; yet 70% of hirers say under half of submissions meet role criteria. The deluge means hiring moves “down to a crawl,” with companies often pulling job posts after a few days to manage the flood. AI tools are a notable contributor: recruiters estimate ~25% more applications are now submitted with AI, and auto-apply services can mass-submit or overstate experience, increasing false matches and signal-to-noise for human reviewers. Contrary to candidate fears, most firms aren’t relying solely on enterprise ATS — manual keyword screening and human review remain common — which amplifies wasted time. For the AI/ML community this highlights two needs: better, verifiable candidate-data pipelines (to prevent misrepresentation) and smarter, calibrated screening models that preserve recruiter trust and reduce bias. For candidates, the practical takeaway is quality over quantity—tailored resumes, networking and referrals still outperform mass AI-submitted applications.