Candidates do not resent AI in hiring. They resent the silence around it.

By Tatiana Teppoeva, PhD, AI hiring risk consultant with Human Signal Advisory

What Candidates Respond Well To

The best experiences never turn on the technology itself. They turn on transparency. Candidates respond well when a company tells them plainly that AI is part of the process and what it evaluates. They also want a real person reachable at every stage so the process does not feel like talking to a wall. And they accept AI when it removes busywork or lets them demonstrate a genuine skill, but they are very sensitive when it is used to score their face or their voice.

Candidates do not resent AI in hiring. They resent the silence around it. Gartner’s Q1 2025 survey of 2,918 job candidates found that only 26% trust AI to evaluate them fairly, and 25% trust an employer less the moment they learn AI is screening them. So, trust and transparency matter enormously and are two very important components of the good experience for candidates. 

Candidates also value understanding how they were assessed. When a company can explain what its tool measured and why, a candidate learns something they can carry forward, even from a rejection. 

What Successful Employers Have in Common

The companies whose candidates walk away impressed are the ones who understand what their own AI tools are doing. This is where most employers get stuck. When a screening tool produces a score and the company cannot explain how it got there, the tool has quietly defeated its own purpose. The reason to use AI in hiring is to make better, and more defensible decisions. A black box does the opposite. The employer cannot tell whether the tool is measuring something job-relevant or something irrelevant, cannot defend the decision to a candidate who asks, and cannot answer for it if legal or a regulator comes calling.

So the employers doing this well insist on understanding the tool before they trust its output. They know what it measures and why. That understanding is what lets them communicate AI use to candidates clearly, explain any decision in plain job-related terms, and stand behind the outcome.

This is now also a legal requirement. Under Colorado’s new AI law, the employer, not the vendor, owns the outcome and has to be able to explain it. 

Why This Matters

In my own testing of multiple screening platforms, I have seen substantial differences in how the same candidate is evaluated across systems. That inconsistency reinforces why employers need to understand exactly what a tool measures before relying on its output. A signal can be measured accurately and still be interpreted incorrectly.

Among students, the resistance is concrete. More than 40% have already declined an AI video interview rather than participate in a process they could not see into, and less than 20% say an employer’s use of AI strengthened their interest in that employer. (NACE/SRG Research, spring 2026)

The companies creating the best candidate experiences are not the ones with the most advanced AI. They are the ones that make the process understandable. Candidates will tolerate automation. What they will not tolerate is uncertainty about how decisions are being made or who is accountable for them.

— Tatiana Teppoeva is an AI hiring risk consultant with Human Signal Advisory™, a former Microsoft and Boeing data scientist for 17 years, eight of which was building AI systems; U.S. AI patent holder; Harvard Master’s in Data Science; and a PhD in Economics