It was 2024, and I was looking for a new job. A helpful yet demoralizing feature of some job boards is a count of how many people have applied to the job. Seeing those figures made it clear that I was going to be one of hundreds of applicants. I felt I had no chance.
So I did what 40% to 70% of candidates do (iHire, 2025; Resume Now, 2025): I used AI to help write my resume. It was easy – I provided my draft resume, the job description, and asked it to revise my resume to better suit the job. After a manual scan to make sure I wasn’t overstating, I used that revised application to apply.
I stand behind what I did because it allowed me to have a fighting chance in a difficult job market and among an enormous number of applicants. Recruiters receive three times the applications today compared to four years ago (Greenhouse, 2025), making an effective talent selection and assessment process more important than ever.
AI is both the solution and the problem
For years, recruiting teams have used AI to combat the issue of being inundated with applications. This technology uses keyword matching to assess the correspondence between a candidate’s resume and the job description. This helped for a while – there was no longer a need to manually review resumes, unless the resume was a top match. But now, these technologies have outlived their usefulness due to the widespread availability of LLMs.
In reality, the challenge isn’t with the technology itself, but with the data. Decades of research in the field of assessments has shown that data points present in resumes like years of experience are poor indicators of job performance (Sackett et al., 2022). Although you could argue that resumes or cover letters give indication of interest in the role and written communication ability, recent research suggests that even that benefit is no longer present, with AI making it easier for low performers to appear competent in resumes (Galdin & Silbert, 2025).
Widespread availability of AI is also making it easier for dishonest candidates to do what they already did before, which is lie in their resumes (StandOut CV, 2025). Even work samples and portfolios can be faked, with 28% of US applicants using AI to do so (Greenhouse, 2025). It is not surprising then that McLean & Company’s HR Trends 2026 survey found that adopting skills-based hiring practices was the highest-implemented emerging trend by organizations, signaling the realization that relying on resumes and stated education and experience is not enough to make quality hiring decisions. To verify skills, you must use validated assessments.
The benefit of assessments
Thankfully, there are plenty of assessment tools in the market (see McLean & Company’s SoftwareReviews for a shortlist of vendors) that have been designed to scale to high volumes of applicants. They help narrow the candidate pool down to which applicants deserve further attention. These assessments work by assessing the knowledge, skills, and abilities (KSAs), also known as competencies, that are relevant to the role, such as coding ability, cognitive ability, conscientiousness, or other personality factors. Notice that these are KSAs that can’t be validly assessed through a resume – they require a more rigorous approach.
Practically, integrating assessments into the hiring process means:
- Conducting a job analysis to determine KSAs required for the job.
- Selecting the assessment that best evaluates those KSAs.
- Piloting the use of the new assessment to evaluate its efficacy.
- Integrating the assessment into the talent acquisition process.
Assessment can be done at scale, to counteract the issue of being flooded with resumes, or at later stages of selection with the final few candidates for a role. AI can even help with the assessment process if it’s implemented thoughtfully, ethically, and with the same rigorous standards that traditional validated assessments adhere to.
As for what happened with me – I was lucky enough to get a referral for my current role, which helped my resume land near the top of the pile. But to land the job, I went through rigorous assessments that targeted the most important KSAs for the role. And in that process, my employers got an in-depth view into my potential, saving me from the AI-assisted resume-writing grind. I’d invite you to also move beyond the fear of AI-generated resumes and adopt modern assessment approaches that drive hiring effectiveness and quality.
To learn more about assessments, visit McLean & Company’s candidate assessment research. If you are interested in learning more about our research and services, please reach out to jcampbell@mcleanco.com.
Works cited
“The 2025 Workforce Survey Report: Mid-Market Edition.” Greenhouse, 2025. Web.
Fennel, Andrew. “How Many People Lie on Their Resume? [Study]” StandOut CV, 25 March 2025. Web.
Galdin, Anais, and Silbert, Jesse. “Making Talk Cheap: Generative AI and Labor Market Signaling.” arXiv, arXiv:2511.08785 [econ.GN], 11 Nov. 2025. Web.
Gebreyes, Micah. “How to combat hiring pipeline overload – and protect your brand.” Greenhouse, 2025. Web.
Kelly, Kristina. “40.7% of Candidates Have Used AI in Their Job Search – But Adoption Varies by Generation.” iHire, 24 June 2025. Web.
Sackett, P. R., et al. (2022). “Revisiting Meta-Analytic Estimates of Validity in Personnel Selection: Addressing Systematic Overcorrection for Restriction of Range.” Journal of Applied Psychology, vol. 107, no. 11, 2022, pp. 2040-2068. Web.
Spencer, Keith. “AI Reshapes Job Hunting: 84% Say It’s Easier to Find Jobs.” Resume Now, 25 Feb. 2025. Web.