Not long ago, a candidate came through our process for a production role. His resume was straightforward: solid production background, nothing that immediately stood out. On paper, he was a Producer. That’s how he would have been categorized and likely screened.
But fifteen minutes into our conversation, I was hearing something different.
He wasn’t describing what he’d made. He was describing how he’d kept everything running: the workflows, the coordination across teams, the resource management, the accountability when things went sideways. That’s not a Producer mindset. That’s a Studio Manager. He just hadn’t worked somewhere that gave him that title.
We hired him into a Studio Manager role. It was the right call, and his resume alone never would have told us that.
I’ve been in recruiting for fifteen years, and this kind of moment still happens regularly. What worries me is how many of those moments are being quietly eliminated as AI screening becomes standard practice at the top of the funnel.
AI is useful in recruiting. We use it at Thinkingbox for drafting job descriptions, summarizing notes, and reducing the administrative work that used to consume a significant part of the day.
But there’s a meaningful difference between using AI to handle work that doesn’t require human judgment and using it to decide who gets a conversation in the first place.
Job titles are not standardized. A Senior Producer at a boutique agency and a Senior Producer at a large network are often doing entirely different jobs. Someone who has spent years in one function may have developed skills that translate directly into a completely different role, but nothing on their resume will surface that. The only way to find it is to talk to them.
This is a structural problem. And it’s exactly why we still review every candidate as a human being rather than a collection of keywords.
According to the SHRM 2025 Talent Trends Report, 43% of organizations now use AI for recruitment and HR activities, and adoption continues to grow. The efficiency gains are real. So is the risk of building a process that’s very good at finding the expected candidate and much less good at finding the right one.
Candidates are paying attention to this too. Gartner data shows 68% of job seekers prefer interacting with a human during the hiring process. A Workday global survey found 93% of hiring managers believe human involvement remains essential even when AI tools are used. When a process feels automated rather than considered, candidates notice. And the strongest ones disengage first.
That’s why we brought in-person interviews back after the pandemic and kept them. Final rounds always happen face to face. Hiring is a two-way decision, and candidates deserve the chance to experience the environment and the people, not just the process. We’ve seen a 16% improvement in retention rates as a result.
What I’ve seen over fifteen years is that the best hires often don’t fit the obvious pattern. They’ve come from adjacent industries, taken unconventional paths, or held titles that didn’t reflect what they were actually capable of. The only way those candidates get through is if someone is paying attention during the conversation, not just running them through a filter beforehand.
AI can make recruiting faster. It can’t make it better on its own. The organizations that get this right will be the ones that use AI to clear the path for human judgment, not replace it.
