What I Fix First When a Client Brings Me an AI-Written Résumé

By Don Pippin, MHRM, CPRW, CDCS, CIC, CPBS

I can usually recognize an AI-written résumé pretty quickly. Most recruiters probably can too.

There tends to be a formula to them. The sentence structure repeats. The bullets all have a similar rhythm. The language gets a little bigger than it needs to be. There are often a lot of perfectly clean numbers like 10%, 30%, or 50%. Everything sounds polished, but after reading it, I still may not know much about the person behind it.

That does not mean I think people should stop using AI for their résumés. I use AI. I have built AI career tools. I think it can be incredibly useful.

The problem comes when people rely on it too heavily and let it make decisions that really require human judgment.

When someone brings me a résumé they have been working on with ChatGPT, Claude, or another AI tool, there is a pretty specific order in which I start pulling it apart.

First, I ask what job you are targeting

Before I worry about wording, metrics, bullet points, or formatting, I ask one question:

What job are you trying to get?

If I cannot look at the résumé and get a pretty good idea of the answer, we already have a problem.

This is probably one of the biggest things people miss when they work on their own résumé. They keep changing the content without really deciding what the résumé is supposed to position them for.

That becomes even more complicated when AI gets involved because AI is very good at improving the material you give it. It does not necessarily know whether that material belongs in the story you should be telling.

Someone can have a beautifully written résumé that tries to position them for operations, strategy, customer success, project management, and business development all at the same time.

The problem is not necessarily that any of those things are inaccurate. The problem is that I do not know what I am supposed to hire them to do.

So before I rewrite anything, we establish the target.

Once I know where you want to go, I can start deciding which parts of your background help us get there and which parts are distracting us.

Then I change the structure

This is probably the fastest way I recognize a résumé that has been heavily written by AI.

AI résumés tend to be formulaic.

The bullets often use the same sentence construction again and again. Accomplishment after accomplishment follows a predictable pattern. The verbs start sounding alike. Sometimes every bullet has been forced into the same accomplishment formula whether the information naturally fits that format or not.

After a while, the résumé stops sounding like a person.

This is usually where I start making fairly significant changes.

Some information may need to become a short paragraph. Other information needs to move into a bullet. Maybe five bullets really contain two good stories. Maybe the first thing listed under a job is actually one of the least important things that person did.

I am looking at how someone will actually read the page, what they will notice first, and whether the structure is helping tell the story.

That is why the résumé I give back to someone can look very different from the résumé they sent me, even when much of the underlying experience is the same.

Then I pressure-test what is actually on the page

This part is really important with AI-written résumés.

I want to know whether the person can explain what the résumé says.

If there is a bullet that says you increased something by 40%, I am going to ask where the 40% came from.

How was it measured?

What was happening before?

What did you actually do?

Who else was involved?

How do you know your work caused the result?

Could you explain this comfortably if a hiring manager asked you about it?

I will often take this a step further during interview coaching and essentially run parts of the résumé through a mock interview.

That is where things sometimes start to fall apart.

A statement may sound great on paper, but the client cannot explain where it came from because AI helped create language around something they vaguely remembered. Maybe there was an improvement, but nobody ever measured it. Maybe the number was an estimate that slowly became a fact after enough rounds of rewriting.

I also pay attention when a résumé is filled with very clean percentages.

10%.

20%.

30%.

50%.

Real business results are not always that tidy.

That does not automatically mean a number is wrong. Plenty of legitimate results happen to be round numbers. But if nearly every accomplishment lands on one, I am going to ask questions.

A résumé has to survive the interview.

If you cannot comfortably tell me the story behind a statement, I do not want to send you into an interview depending on it.

After that, I start looking for the generic language

Once I know the résumé is targeted correctly and I trust what is on the page, I start looking at the content itself.

This is usually where I see another common problem with AI.

Everything may be technically fine, but it is incredibly generic.

The person "drove cross-functional collaboration."

They "optimized operational efficiencies."

They "leveraged strategic insights."

They "spearheaded transformative initiatives."

I read a lot of résumés. None of that tells me very much.

And sometimes the client does not have metrics. That is okay. Not every accomplishment comes with a percentage, dollar amount, or headcount.

What I need instead is context.

So I start asking them to tell me stories.

Tell me about a project you worked on.

Why did it exist?

What was going wrong?

What did you walk into?

What did you change?

Who cared about it?

What made it difficult?

What did you do differently from the person who had the job before you?

What happened afterward?

Those conversations are where the résumé usually starts getting good.

People remember things when you talk to them that they would never think to type into an AI prompt.

Sometimes they casually mention something halfway through a story and I stop them because that is the thing I have been looking for.

They did not think it was important because they were there when it happened. To them, it was just part of the job.

To me, as someone who has recruited and hired people, it may be the thing that makes them stand out.

A unique résumé usually comes from context, not better adjectives

This is probably the biggest difference between rewriting and résumé writing.

If you give AI a generic statement and ask it to make it stronger, it can usually make the sentence sound better.

But a stronger version of generic information is still generic information.

What makes a résumé unique is usually the context behind the work.

Two people can have the exact same job title at competing companies and have completely different stories to tell.

One may have inherited a struggling team and rebuilt it.

One may have been brought in during rapid growth.

One may have created processes that never existed before.

One may have spent most of their time developing people.

One may have become the person senior leadership called when something went wrong.

That is the information I am trying to uncover.

Once I understand that, the writing becomes much easier because now there is actually something worth writing about.

I may use very little of the résumé you gave me

Clients are sometimes surprised by this.

They may have spent weeks working on a résumé with AI, refining it over and over, and then I use very little of the actual wording.

That does not mean all of that work was wasted.

It often gives us raw material. It helps surface projects, responsibilities, numbers, job history, and ideas that we can explore.

But by the time we establish the target, restructure the document, validate the claims, and dig into the real stories, the final résumé can be substantially different.

That is usually the point.

I am not trying to make the AI version prettier.

I am trying to figure out the strongest, most accurate way to position the person behind it.

So should you use AI to write your résumé?

I think you should use whatever helps you get started.

Ask AI to help you brainstorm. Use it to organize your thoughts. Have it ask you questions about an accomplishment. Let it help you get through the blank-page stage.

Just do not assume that because the writing sounds polished, the résumé is finished.

A résumé still needs a target. It needs structure. It needs facts you can defend. And most importantly, it needs enough of your actual experience and context that the person reading it understands why you are different from everyone else applying for the same job.

That is the part I spend most of my time working on.

And it is usually the part that changes the résumé the most.

If you have been working on your résumé with AI and it still does not feel right, learn more about Human Résumé Writing or area|Talent Résumé Writing Services.