A job applicant deployed ChatGPT Voice to respond to Riley, an AI recruiter from IT staffing firm Everforth Apex Systems, after four automated interactions yielded no human follow-up and no rejection notice. The 10-minute bot-to-bot call—which the applicant recorded and shared—exposes a structural flaw in how some companies deploy hiring automation: the system generates engagement signals without converting them into filled positions or revenue.
The applicant, who requested anonymity because he is still job hunting, had applied to roughly 700 positions over six months as his government contracting work dried up. Five applications routed through Riley, which promised human recruiter contact if his qualifications met the company's bar.
After the fourth interaction produced no human response and no rejection, the applicant fed ChatGPT his resume and background, instructed it to pose as him, and placed his phone next to the AI during Riley's fifth call. The two systems became stuck in a loop discussing "standard onboarding and background checks" without resolving a start date. Riley ended the call with "great talking to you." ChatGPT replied that it appreciated "how clear and straightforward the process was." No human recruiter followed up.
The applicant described the dynamic as a "slop flywheel"—synthetic data flowing between synthetic personas toward no operational end. He said the experience killed any interest in working for the company.
Everforth Apex Systems did not respond to requests for comment.
The incident highlights a blind spot in AI hiring economics: volume of interactions does not equal hiring volume, yet many vendors price and market their systems on throughput. When a recruiter bot can engage with hundreds or thousands of candidates without human oversight or conversion tracking, the company accrues data and engagement metrics that feel productive but may reflect only automated busywork.
Voice-based AI recruitment introduces additional technical friction. These systems often stumble on accents, filler words like "um," and conversational norms like turn-taking—the kind of human communication nuance that turns a scripted exchange into a hire.
