Everyone has an opinion about AI in hiring. Some see it as a dangerous shortcut that reinforces bias.

Others treat it like a silver bullet that's smart enough to do what recruiters and hiring managers never had the time to. But as it turns out, the most powerful application of AI in candidate assessment is much more grounded: empowering humans to make better decisions.

Across dozens of companies and hiring contexts, one theme is emerging. AI isn't replacing the judgment of recruiters. It's amplifying it.

Why candidate assessment is ripe for reinvention

If you’ve ever tried to scale a hiring process, you know the pain. Hundreds of resumes. A handful of good ones. Hours lost to interviews that go nowhere. And behind all of it, one nagging question: “Is this person actually right for the job?”

Hiring assessment tools were supposed to help. But for years, they did little more than filter candidates through rigid tests that didn’t reflect real work. Candidates hated them. Hiring managers ignored them. Recruiters were stuck in the middle.

Then AI changed the landscape, not by adding more automation, but by rethinking how we evaluate skills in the first place.

AI works best when it's used to augment and not replace humans

The early promise of AI in hiring was seductive. Train a model to recognize high performers based on your historical hiring data, and let it screen candidates for you. No bias. No fatigue. Just efficiency.

In reality, that approach proved risky. AI trained on flawed human decisions tends to reproduce those flaws at scale. The Amazon resume screening software debacle is the textbook example—but it's far from the only one.

The more sustainable approach is to use AI to make recruiters more effective, not obsolete. Think AI-generated interview questions for roles you’ve never hired before. Automated note-taking so you can focus on the conversation. Summary reports that surface candidate insights without forcing you to rewatch the entire interview.

It’s not about outsourcing decisions to AI. It’s about giving recruiters the tools to make better ones.

The rise of high-context, high-fidelity technical assessments

One of the most interesting applications of AI right now is in technical hiring. Tools are shifting the assessment paradigm from “did they get the right answer?” to “how did they approach the problem?”

Instead of relying on outdated multiple-choice tests or generic coding questions, new AI software lets you paste in a job description—and it generates a custom coding challenge that mirrors the work the candidate would do on the job. AI tracks not just whether they completed the task, but how they navigated it: Did they explore the codebase? Did they refactor intelligently? Did they Google or use ChatGPT strategically?

The goal isn’t to penalize candidates for using AI. It’s to observe how they use it—because that’s exactly what they’ll be doing on the job. It’s not cheating. It’s how modern work gets done.

Fairness, transparency, and the ethics of AI

As AI becomes a bigger part of hiring, it raises a critical question: How do we make sure it’s fair?

The answer, at least in part, lies in how we design our AI candidate assessments.

A technical challenge that reflects real work is inherently more equitable than a brainteaser designed to trip candidates up. And when AI is used to evaluate candidates, it needs to be grounded in objective criteria.

If you're using AI to assess candidates, say so. Let them know how their work will be reviewed. Better yet, ask them to document how they used AI in the process. Did they use it to structure their response? To debug? To draft an outline?

AI can be a tool for de-biasing—but only if we use it responsibly.

Assessments are everywhere now and candidates know it

One of the more telling anecdotes came from a recent discussion with a fellow founder. Her son, a Gen Z jobseeker, applies for roles by pasting the job description into ChatGPT, attaching his resume, and asking the bot to tailor it. Then he submits and waits.

This isn’t unusual. It’s the norm. As hiring teams build AI into their toolkits, candidates are doing the same. And just like recruiters, they’re not necessarily wrong to do so. The playing field is changing fast. Your process needs to keep up.

Assessment usage has exploded with over 60% using hiring assessments today. But many of those assessments still reflect outdated assumptions. They're rigid, easily gamed, and disconnected from what the job actually requires.

What candidates want isn’t fewer assessments. They want assessments that respect their time, reflect the role, and give them a fair shot to show what they can do.

What this means for recruiters

So what’s the takeaway for TA leaders in 2025?

• Use AI to accelerate research and prep but keep human judgment at the center
• Prioritize assessments that mirror real work over abstract puzzles
• Allow candidates to use AI and evaluate how effectively they use it
• Communicate clearly about your use of AI, especially in evaluations
• Continuously iterate on your assessments to reflect role changes and market trends

Most importantly, don’t get caught in the “AI vs human” trap.

The most effective hiring teams are thinking differently: How can AI reduce friction in the process? How can it give us deeper insight into candidates? How can it help us focus more on what matters—real conversations, informed decisions, and stronger teams?

Because when you use AI to make hiring more human, everybody wins.