74% of Hiring Managers Have Already Caught an AI-Written Sales Resume

Dave Kurlan, writing on Objective Management Group’s Understanding the Sales Force blog, argues resumes are an increasingly unreliable tool for evaluating sales candidates, and that generative AI is making the problem worse rather than causing it. He cites Leadership IQ research finding 46% of new hires fail within 18 months — with 89% of those failures driven by coachability, emotional intelligence, motivation, and temperament rather than technical skill — and that 40% of senior hires fail within the same window. Layered on top: 74% of hiring managers have already encountered AI-generated resumes, and 75% of job seekers now use AI tools to apply for jobs, meaning a polished resume increasingly signals AI assistance rather than a candidate’s real capability. Kurlan estimates a failed sales hire costs a company $250,000 or more, and recommends front-loading predictive, sales-specific assessments early in the funnel — before resume polish or interview charisma can mislead evaluators — while reserving AI for recruiting logistics rather than candidate judgment.

The resume problem is really a proxy for a hiring-signal problem that shows up elsewhere in sales leadership too. SaaStr’s Jason Lemkin has made a related argument about VP of Sales and CRO hiring specifically: picking a candidate because the whole team likes them is, in his estimate, wrong roughly 9 times out of 10, because both weak and strong performers alike resist a genuinely capable leader who threatens their position, and board members steer founders toward candidates who “sell up well” rather than candidates suited to the company’s actual go-to-market motion. Kurlan’s resume data and Lemkin’s likability data point at the same underlying failure: the signals sales organizations have relied on for decades — a clean resume, a well-liked interview — were never that predictive, and AI is now degrading the resume one specifically, fast enough that hiring processes built around it need to change before the next cycle, not after another $250,000 mistake.