Signal Lost: The AI Hiring Arms Race, the Applicant Flood, and How Leaders Can Restore Trust and Validity in Selection

Abstract: Generative artificial intelligence has changed both sides of the hiring process at once. Candidates now use AI to write, tailor, and submit applications at scale, while employers increasingly use AI to screen the resulting volume. Workday's October 2026 Global Workforce Report found that 84% of job seekers used AI in their search and that the median number of applicants per filled job rose from 58 to 69 in a year, with no improvement in time to fill. This article examines the resulting arms race: a flood of polished but less informative applications, rising candidate fraud, falling trust on both sides, and growing legal exposure for automated screening. Drawing on personnel selection research, labor economics, algorithmic fairness studies, and regulatory developments, it explains why traditional application signals are losing value. It then reviews five evidence-based responses: redesigning the front door around skills, shifting weight to high-validity assessment, verifying identity proportionately, governing AI screening tools, and adopting transparent AI policies for candidates. It concludes with a framework for treating hiring as an evidence-based measurement system.