“Staid.” That’s how the Washington Post recently described the job market — not specifically in crisis, but the labor force is shrinking, and hiring is relatively anemic compared to the incredible growth seen after the ebbing of COVID. The unemployment rate in the U.S. ticked up from the 3-4 percent range in 2022-2024 and settled at around 4-5 percent in the last few years, with outside shocks like tariffs, wars, and the AI revolution hammering many industries. Silicon Valley has seen over 123,000 layoffs this year, according to Forbes, with generative AI cited as the main reason behind the cuts.
If AI is one of the problems bedeviling the job market, it’s also seen by some as a solution. More than half of jobseekers utilize AI to write their resumes and cover letters, according to a LinkedIn survey. Employers are even more keen on using AI to screen candidates, with nearly 90 percent using it to rank or filter resumes, according to the World Economic Forum.
Making your resume and cover letter attractive to AI is much simpler than trying to slip in hidden words or prompts as some jobseekers have done (many employers now have software that catches those tricks, reports the New York Times).
Mashable connected with a handful of career experts on how to (ethically) get your resume to the top of the algorithms’ piles. Our first expert, Jasmine Escalera, PhD, is a career coach who advises recruitment companies like Zety and Bold. Escalera said to keep it simple when it comes to your resume — and don’t forget that human eyes will eventually be looking at your CV and cover letter.
So many people assume AI is doing the first pass on resumes. Is that true?
It’s likely the case. We know the job market is very flooded. We know it’s a very challenging job market. We’ve seen jobs posted on LinkedIn, and within hours, they have hundreds of applicants.
AI, if it’s used by a company, is a first-round filter — to essentially be able to say, out of these hundreds of applicants, which no HR human could really go through on their own, how can we find the applicants that match the position the best?
So, in the second round, humans, individual eyes, can come onto the best talent within this pool and really see who can move forward with the interview process.
So, yes, and I know that can be very frustrating for job seekers, but we also want to understand the recruitment process. Because of the job market and how challenging it’s become, HR and recruiters are using [AI] to really filter through a very large applicant pool.
Is there an argument to be made that AI levels the playing field? Instead of a human sifting through a pile of resumes and seeing someone who went to their alma mater, it’s a computer without those biases.
Well, I remember when I was a jobseeker back in the day, when these kinds of AI tools didn’t necessarily exist — there were applicant tracking systems, but they didn’t work the way they do now. We were told, “Apply for a job on a Monday morning or even a Sunday night, so your application is at the top of the list.” Or, “Don’t apply on these particular days.” We were trying to come up with workarounds to get ourselves seen.
Now, the inherent bias sort of gets taken out of the occasion. Because every jobseeker now knows they have to get through the [Applicant Tracking System] and is using AI to help support them in resume building, it’s made it that much more complicated because now everybody knows what a keyword is, everyone knows what skills they need to put on a resume, everybody can use AI to help generate the most stellar bullets to stand out with quantifiable metrics. It’s made it much more challenging, and that’s why AI can be most helpful in filtering through this [for HR professionals].
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But, ultimately, it is a filter. When you get to that human who’s looking at your resume, they’re likely going to be looking for something completely different than what the AI was looking for. Baseline, [at that point] they know the applicant pool is going to be stellar, that these applicants likely have all of the experience and skillsets they set [the AI to look] for. Now, what they’re looking for is differentiators. What differentiates resumes A, B, C, D, E, F, and G? And those differentiators are typically the things AI can’t create for you.
Does AI have a bias against resumes created with AI?
It’s very dependent on whatever system the employer is using, and I don’t have enough knowledge to know if these AI systems these employers use have triggers for AI-created resumes. However, there are AI tells.
There are specific ways AI creates resumes that tell whether AI just completely generated this. It’s a lot of amplification of the experience. They have so much jargon there; [the job descriptions make] you sound like you went to the moon. There’s a lot of extra words and verbiage.
So we want to make sure that if you are using AI, and I believe every jobseeker should use AI to support them in resume building — support is the key word — you have to go through and make sure this sounds like a human created it, there’s that human element to it, there’s storytelling involved in it. You can’t create a story-based resume that focuses on why you’re specifically perfect for this mission because, at the age of 10, you were baking cookies and selling them, and now you want to work for the Girl Scouts and sell and market their cookies.
There are so many sites that claim to help jobseekers optimize their resumes for AI. Can those websites be trusted?
It’s really about the research and looking into the different platforms you’re interested in and making sure other jobseekers have used it and had success with it. Just like if you were to purchase any kind of product, you’re going to want to know if that product is going to give you the best bang for your buck. A jobseeker should do the same due diligence when it comes to the platforms that help them build their resumes.
The great things about Claude, ChatGPT, and AI in general, outside of the AI resume builders, are that they can help you create these bullets of experiences and skill sets. Some of these other AI resume builders are really built to help you create the layout, the architecture, the design of the resume. That’s one thing to consider.
Cover letters are even more important now because that’s the opportunity to tell a story.
Any tips for making resumes stand out to the algorithms?
The number one thing is to make sure you’re using the job description as the template for your resume. You want to make sure the job description in your resume matches very closely, meaning the term they’re using, you’re using.
If you’re applying for a client success manager position, but you’re using “customer success manager,” even that small keyword switch is going to make a difference. Follow the job description to a T. Typically, whatever bullets they have at the beginning of the job description are usually the most high priority items for this position, in terms of experience, knowledge, and showing you’re capable of doing those tasks.
A great thing to do is to take that job description and put it through a Claude or a ChatGPT and ask it specifically, “What are the key words I should make sure are in the resume? What are the top experiences or work tasks this job is asking me to focus on?”
We’re talking about resumes, but one of the biggest things that people often ask me is, “Do you really need a cover letter?” People hate cover letters. And now, because resumes can be so well-crafted and so well-generated with AI, I believe cover letters are even more important because that’s the opportunity to tell a story. That’s the opportunity to say why this organization matters to you so much.
You also want to think about those differentiators — what’s going to make me stand out in the resume? Where can I add specific elements that will really connect with this organization’s mission, and how can I use my cover letter to tell my story as well?
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This interview has been edited for length and clarity.
