If you’ve hired, you’ve probably been here: after parsing hundreds of resumes, you’ve narrowed your search down to a small handful of highly-qualified candidates. Each possesses a different combination of strengths and weaknesses: one may check all the right boxes, but struggles to communicate their thoughts clearly. Another has excellent emotional intelligence and a growth mindset, but has some concerning skills gaps. Any one of these finalists could do the job, but none are 100 percent ideal.

Hiring has always been an imperfect science, but it also comes with sky-high stakes. Get it right, and you’re adding someone who can push your team and organization forward in ways you may not have even expected. Get it wrong, and you're looking at misalignment, a costly rehire process, and—if you're not careful—lasting damage to your team culture.

I’ve been hiring at Jotform for nearly 20 years, and to this day, it’s still one of the parts of my job I take most seriously . In that time, I’ve made some excellent hires, and honestly, I’ve also made some awful ones. And while hiring is never a job I will outsource, AI can be a very useful thought partner when it comes to quieting the noise and making the right choice. Here’s how.

The Psychology Of Tough Choices

There’s a reason that hiring keeps leaders up at night. Decision paralysis is a real psychological phenomenon, and it’s easy to feel overwhelmed in the face of too much information.

It makes sense, then, that when making tough decisions, we tend to default to binary choice making, which potentially cuts off other, better options. The simplicity of two options is easier to cope with than, say five—even if the outcome is worse as a result.

The problem is that humans are much better at making consistent decisions when they directly compare options side by side, as opposed to rating multiple options subjectively. But hiring is almost always the latter scenario. You’re assembling impressions across different days, times and circumstances, and trying to synthesize them into one preferable choice.

And of course, humans are biased. We are swayed by subconscious gestures that ultimately have no bearing on a person’s ability to do a job, like poor posture or a weak handshake. Obviously you want any new hire to be an organizational fit. What you don’t want is to discount someone because they didn’t smile enough, or you hated their shoes.

How AI Can Help Cut Out Bias

No one likes to think of themselves as biased, but it’s not always up to us. Unconscious bias is a form of mental shorthand that allows your brain to categorize information quickly—the problem is, it often happens at the expense of accuracy. There’s a famous riddle you may have heard about a father and son who get in a car accident; the father dies at the scene and the boy is rushed to a hospital. Once in the operating room, the surgeon looks at the boy and exclaims, “I can’t operate on this boy, he’s my son!” If you posited that the father’s ghost was conducting the operation before it occurred to you that the surgeon was actually the boy’s mother, this is unconscious bias in action.

AI is biased, too—it is, after all, trained on vast amounts of human-generated data, meaning it reflects human biases. That’s why we shouldn’t let it make hiring decisions for us.

Deployed correctly, however, it can help us identify our own leanings. Researchers at Cornell, for example, recently built a tool specifically to uncover unconscious bias by asking users to identify what they value by weighing different criteria; the tool then locates the points at which the values and rankings contradict. “If there are contradictions, the user can change their ranking or try to justify it with new criteria, but either way, they are forced to provide a clear and consistent explanation for their choices,” one of the researchers explained.

But even LLMs like ChatGPT or Claude can help identify biases. Feed your interview notes across multiple candidates into an LLM, and ask it to point out where your assessments became inconsistent. Sentiment analysis can show where your language veers away from job criteria alone, and flag contradictions in your reasoning.

A Fact-Based Alternative To Gut Feelings

A lot of the time, hiring comes down to a gut feeling. But it shouldn’t. All too often, hiring decisions are made based on answers to unquantifiable questions rather than a concrete strategy or tested process, writes Forbes contributor Chad Biagini. But “what do you think would happen if other areas of the company functioned without processes?” he asked. “Can you imagine your CFO using their gut rather than financial data to make financial forecasts?”

Here’s another place where AI can help. Use it to generate a standardized set of interview questions tied directly to the competencies the role requires. Have it build a scoring rubric your whole team uses, so that "strong communicator" or "strategic thinker" means the same thing to every interviewer in the room. Ask it to summarize each candidate's responses against the same criteria and in the same format, so you're comparing like with like rather than trying to weigh one person's charisma against another's technical depth.

When it comes to a final call in hiring, a human should always be in the driver’s seat. But AI can help us defend us against our own blindspots, leading to smarter hires and better outcomes.