Artificial intelligence has been one of the most influential forces shaping recruitment in a global talent war. The volume of data companies can now access, the speed at which candidate pools can be filtered, and the complexity of searches that can be executed in minutes; these are all genuine advances. Yet amid the enthusiasm surrounding automation, Michael Ronis, founder of Janbrook Partners, believes many companies are asking the wrong question.

“AI opens a lot of doors in the sense of access to information,” Ronis says. “You can now research things and approach searches in a much more complex way than you could in the past. The real game changer is the access to information and the ability to break down information.”

Ronis argues that the debate today is largely focused on whether AI can replace recruiters. He rejects that conversation entirely. Instead, the more vital consideration, in his view, lies in a single question: at what point does a human step in?

Recent surveys show that 88% of employers now incorporate AI to accelerate talent acquisition and candidate screening. The appeal, he notes, is easy to understand as the volume problem alone makes some degree of automation non-negotiable. With companies receiving over a million applications in a year, Ronis notes that AI, at that scale, becomes a necessity, as it would be nearly impossible to manage that quantity manually.

Ronis has experienced that reality firsthand. “We ran an ad for a remote recruiter position and got a thousand resumes in a matter of hours,” he says. “At that point, give me the AI.”

Yet he believes the industry has conflated efficiency with effectiveness, and the financial consequences of that, Ronis adds, are catching up. Replacing an employee can cost anywhere from 50% to 200% of their annual salary, once recruitment fees, onboarding, training, and lost productivity are factored in. At the same time, Ronis observed that employee turnover continues to challenge employers across industries, particularly during the first year of employment.

According to Ronis, recruitment should not be measured solely by how quickly a role is filled. The more meaningful metric is how successfully that hire performs and remains with the organization over time.

Many companies focus on reducing hiring costs through automation, he argues, while paying less attention to the financial consequences of poor retention. “If you automate things to the extent that you overlook cultural fit, you wind up with a situation where you buy it cheap and buy it twice,” Ronis says.

His concern is not that AI lacks analytical capability. Rather, it lacks the ability to evaluate the nuanced human dynamics that often determine whether a candidate succeeds. “At the end of the day, recruiting is relationships,” he explains. “The numbers can get you so far. They can’t replicate rapport. They can’t give you some of the things that hiring decisions are ultimately made of.”

Those dynamics become increasingly important as candidates move deeper into the recruitment process. AI may identify qualifications, rank applicants, and surface relevant profiles, but Ronis points out that it cannot reliably determine a candidate’s level of commitment, career motivations, interpersonal style, or alignment with a company’s working environment.

“You can wind up deeply in the process with someone who might not be all that interested, or who has wildly different salary expectations,” Ronis says. “AI can only do so much. At a certain point, you have to take over.”

Trust also plays a role. As organizations increase their reliance on automated systems, Ronis believes many job seekers have grown skeptical about whether applications are receiving meaningful consideration. “The candidates don’t trust the process,” he says. “They don’t believe their resume is being seen a lot of the time.”

In his view, this growing perception can create challenges for employers seeking to build strong candidate relationships. This erosion of trust can have consequences for employer reputation and candidate engagement, particularly in competitive hiring markets where top talent often has multiple options.

Ronis views cultural fit as another area where human judgment remains indispensable. Every organization has unique interpersonal dynamics and workplace expectations that cannot be fully captured through algorithms or keyword matching. “There are dynamics that underlie every office environment. You have to find the balance where it fits. That’s what the hiring process is really about in the first place. Finding the person who fits the role the best,” he explains.

From his perspective, the strongest recruitment strategies are built around understanding how both can complement one another. AI can accelerate research, uncover patterns, and help recruiters navigate overwhelming volumes of information. Meanwhile, human professionals can contribute judgment, intuition, relationship-building skills, and the ability to assess qualities that may not appear on a resume.

Ronis remarks, “The difference is the human being behind it. Just because the information exists doesn’t mean it automatically creates the right outcome.”

Recruitment has always been about finding the right person, not simply processing applications faster. Technology may improve the search, but Ronis emphasizes that discernment remains the element that turns a candidate into a successful long-term hire.