SPEAKER_00 0:00

Welcome back to HR Echo, the show about what is actually changing in hiring and work. I'm Alex.

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And I'm Jordan. Today we're talking about the strangest development in hiring right now. Somehow, every applicant has become an exceptional communicator with a passion for innovation.

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Usually with a proven track record of delivering results in fast-paced environments.

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Of course. Nobody simply managed a project anymore. They spearheaded a cross-functional initiative that unlocked measurable value.

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Which is impressive until you realize 12 other resumes in the same stack use almost the exact same sentence.

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That's the AI effect. Candidates have access to tools that can rewrite a resume in seconds, tailor it to a job description, draft a cover letter, and prepare answers for an interview. Recruiters are using AI too, to write job descriptions, search for candidates, summarize applications, and sometimes conduct the first interview.

SPEAKER_00 1:02

So we have machines helping candidates talk to machines helping employers.

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And both sides are starting to wonder whether the person on the other end is real.

SPEAKER_00 1:12

Is that an exaggeration, though? People have always asked friends to review resumes. They use templates. Professional resume writers existed long before generative AI.

SPEAKER_01 1:23

That's true. And using AI isn't automatically dishonest. If someone has strong experience but struggles to organize it, a tool can help them communicate more clearly. It can also help people writing in a second language. Those are real benefits.

SPEAKER_00 1:39

Then where does it become a problem?

SPEAKER_01 1:41

When the tool stops clarifying the candidate's experience and starts replacing it. There is a big difference between rewriting a true accomplishment and inventing one. The problem is that AI makes both equally easy to present in polished language.

SPEAKER_00 1:56

And polished language used to be a signal.

SPEAKER_01 2:00

Exactly. A thoughtful cover letter once suggested that somebody had taken time to understand the role. Now it might mean they pasted the job description into a generator 30 seconds ago.

SPEAKER_00 2:12

Which explains why candidates say, I applied to a hundred jobs, while recruiters say, We received a thousand applications and can barely find 10 relevant people.

SPEAKER_01 2:24

Application volume has increased, and not by a little. Greenhouse put recruiters at roughly four times the annual application volume they were handling in 2022. But more volume doesn't automatically create more useful information. If applying takes three clicks and tailoring takes one prompt, candidates can send far more applications than they could a few years ago. Absolutely. This isn't a story where one side is behaving badly and the other side is innocent. Candidates face long forms, repeated questions, automated rejections, and very little feedback. Employers face huge applicant pools, duplicate applications, exaggerated skills, and sometimes entirely fabricated identities.

SPEAKER_00 3:16

So each side automates because the other side automated.

SPEAKER_01 3:21

Right, and that creates a loop. More automated applications lead to more automated screening. More automated screening encourages candidates to optimize harder for the system. Eventually, the process becomes very efficient at moving documents around and not necessarily better at matching people with jobs.

SPEAKER_00 3:40

Let's talk about resumes specifically. Can recruiters really tell when one was written by AI?

SPEAKER_01 3:46

Not reliably, and I don't think trying to detect AI writing is the right goal. A good recruiter should care whether the information is accurate, relevant, and supported by evidence. A candidate could write a terrible resume without AI, or a very good, completely honest one with it.

SPEAKER_00 4:06

Still, there are patterns.

SPEAKER_01 4:08

There are. Much more valuable. Generic professional language is now almost free. What remains valuable is detail that comes from actually doing the work. What was broken? What options you considered? What went wrong? What you personally changed, and what happened afterward.

SPEAKER_00 5:09

That's probably good advice for candidates. Don't try to sound more impressive than everyone else. Try to sound more real.

SPEAKER_01 5:16

Exactly. Instead of writing improved customer satisfaction through strategic initiatives, explain that support tickets were taking four days, you changed the routing process, and the response time fell to one day. The second version gives an interviewer something to discuss.

SPEAKER_00 5:35

What about matching keywords? Candidates are constantly told that if the resume doesn't use the exact language from the job description, the system will reject it.

SPEAKER_01 5:45

Candidates should use the normal language of their profession and make relevant skills easy to find. But trying to reverse engineer an imaginary robot can make the resume worse. Stuffing every phrase from the job description into the document may get attention for the wrong reason.

SPEAKER_00 6:02

Especially if the candidate lists six tools they've barely opened.

SPEAKER_01 6:07

Right. If a skill matters enough to put on the resume, be prepared to talk about how you used it. A smaller list with credible context is stronger than a wall of keywords.

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Employers have responsibilities here too. Some job descriptions read like they were generated from five other job descriptions and never reviewed by the hiring manager.

SPEAKER_01 6:28

That's a major part of the problem. If the employer publishes a vague, inflated description, it receives vague, inflated applications. A clear posting should explain what the person will actually do, which requirements are essential, which are optional, who they work with, and how success will be measured.

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Instead, we get rock star, self-starter, and must thrive under pressure.

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Which often means the company hasn't decided what it needs.

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Now we're seeing AI interviews become more common. How different is that from an automated resume screen?

SPEAKER_01 7:04

More common is an understatement. Greenhouse surveyed close to 3,000 active job seekers this year, and 63% had already been interviewed by an AI. That's up 13 points in six months.

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And how do people feel about it?

SPEAKER_01 7:20

Not good. 70% were never told up front that AI would be evaluating them, and only about a quarter trusted to judge them fairly. Which makes sense because it feels much more personal than a resume screen. Answering questions to a machine can be uncomfortable, especially when the person doesn't know how the recording will be evaluated. Is it analyzing the words, the voice, eye contact, pauses? Candidates deserve a clear explanation.

SPEAKER_00 7:52

And a way to request a human alternative if the format creates an accessibility problem.

SPEAKER_01 7:58

Absolutely. Employers remain responsible for fair decisions, even when software is involved. AI can support a process, but it doesn't absorb the legal or ethical responsibility for that process.

SPEAKER_00 8:11

I also wonder whether automated interviews select for people who are good at performing for a camera rather than people who are good at the job.

SPEAKER_01 8:20

That's the risk whenever the assessment is too far removed from the actual work. If you're hiring an accountant, a structured work sample may tell you more than a perfectly polished video answer. If you're hiring a manager, give the candidate a realistic situation and ask how they would handle it.

SPEAKER_00 8:39

So is that where hiring is going? More tests and more verification?

SPEAKER_01 8:45

Probably, but hopefully better design verification. I expect more structured interviews, practical exercises, portfolio reviews, and questions about specific decisions. Not because every candidate is suspected of cheating, but because a polished document alone carries less information than it used to.

SPEAKER_00 9:05

That could make hiring slower.

SPEAKER_01 9:07

It could. Honest is essential. Robotic is forgettable.

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And what would you tell employers?

SPEAKER_01 10:17

Be transparent about where AI is used. Make the application proportional to the job. Define evaluation criteria before reviewing candidates. Verify important claims consistently instead of relying on instinct. And make sure a human can challenge the system's recommendation.

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Because the real issue isn't whether AI participates in hiring, it already does.

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The issue is whether it improves the signal or just increases the noise.

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That's a good place to leave it. AI can make a resume cleaner, an application faster, and recruiting more efficient. But once every candidate sounds perfect, perfection stops telling us anything.