The Talent You’re Missing: How AI Excludes Qualified Candidates

AI is rapidly transforming recruiting.

According to the World Economic Forum, more than 90% of companies use AI for candidate screening. These new tools have seamlessly integrated themselves into applicant tracking systems (ATS), allowing hiring managers to only view a handful out of the hundreds or thousands of AI pre-screened candidates.

The data: what employers say

But how do we know AI’s doing its job properly screening out the unqualified candidates and floating the best to the top of the pile? Well, we don’t and hiring managers agree.

In a Harvard Business Review study, a staggering 88% of employers say automated screening systems disqualify viable candidates. The numbers get even worse for middle-skills (94%) and high-skills candidates (92%).

It leaves one wondering why companies continue to use these systems, but the sad reality is it’s often because talent acquisition teams have no choice. They’re willing to sacrifice qualified candidates being filtered out because they’re already overwhelmed managing the huge flow of applications from online job boards, especially as the labor market cools. In their eyes, it’s easier to let AI do the heavy lifting and hope the interview process weeds out the pretenders and shines on the stars.

How AI’s being used and its core problems

The most common AI use from hiring teams that we’ve seen is taking a human-written job description and simply copying and pasting it into an AI tool. It can then be instructed to filter, rank and score resumes based on how it matches up against the description. While this is the simplest and most efficient way to use an AI tool, it’s also highly flawed.

The three most common examples of where it can go wrong:

1. Over reliance on very rigid and specific parameters like precise skills, degrees and employment gaps. Let’s say a job description has a strict requirement of needing to have previously led a brownfield transformation. However, a resume that explains the candidate’s background in updating and improving existing systems without explicitly saying the word “brownfield” might get filtered out or downranked.
   
   This is also quite common when it comes to majors and degrees. With many senior roles requiring at least a bachelor’s degree, ATS and AI need robust functional knowledge because of the many variations of how degrees, certifications and trainings are named.
   
   
2. Use of proxies (degrees and certifications, skills, etc.) for soft attributes (work ethic, self-efficacy, etc.). It should probably come as no surprise that a digital tool struggles to completely understand the complexity of a human based on words on a resume – and this is where soft skills are most visible. Any good recruiter can screen beyond the buzzwords and locate desired qualities like servant leadership, accountability and a people-first mentality.
   
   
3. Automated exclusion of candidates who don’t match every criterion – even if they could succeed with training. Not all requirements are created equal. Some are absolutely necessary, preferred or nice to have. Depending on how a resume’s constructed, AI ranks what it detects and sometimes tosses a candidate because a nice-to-have or preferred requirement isn’t determined. It might not realize that person could grow into it based on prior experience and on-the-job learning capabilities.

One recent tactic that’s still in its infancy – yet growing – is the use of autonomous AI interviewers to speak with candidates. Employers say the benefits include reducing the workload of their human recruiters and being able to highly customize the interview questions.

But for companies hiring individuals higher up the org chart, having an AI bot handling the interview leaves a bad taste in the mouth of the candidate. If a leadership talent doesn’t think they’re important enough to speak to a real person, it’s unlikely they’ll consider joining that company down the road. Changing jobs is one of the most significant decisions a person makes in their life, so leaving a key part of the process in the hands of a bot doesn’t give an A-player a vote of confidence.

How candidates use AI

Candidates are well aware their resumes are likely being screened by an AI tool. In fact, it’s now becoming more common for them to use AI to construct tailored resumes and cover letters based on the job descriptions, creating an AI vortex where the entire process from both the employer and candidate becomes smoke and mirrors.

In the 2025 AI and the Application Report from Resume Now, 55% of hiring managers say candidates are using it in this way. This overuse of AI results in the loss of nuance and individuality in applications, making it even more difficult for hiring managers to know what’s real.

There’s a place for AI

We’re not saying AI should be nowhere near the hiring process, but instead a more balanced approach works best. When hiring senior leaders, AI is great for administrative tasks instead of candidate evaluation, screening, interviewing and one-to-one communication.

Online job boards are easy plug-and-play solutions that can ultimately create more challenges than solutions for talent acquisition professionals.

If you’re responsible for bringing in functional leaders, having the experts on your team who are well versed in that sector will go a long way to increase hiring efficiency and ensure the best candidates make it on your team.

Interested in a smarter, more human approach to transformation leadership recruiting? We've got you.