Beyond the Resume: How AI is Shaping the Future of Hiring

IN THE NEWS
How are hiring teams coping with the influx of AI-generated job applications?

According to recruitment company Career Group, 65% of job applicants now utilize AI to assist with their applications. This trend enables candidates to submit a higher volume of applications in a shorter time frame leading to a significant rise in applications. For instance, UnitedUs, a branding agency, reported a 173% increase in applicants for a senior strategist role compared to the previous year. This influx has led to concerns about the authenticity and quality of applications.

Despite some employers explicitly banning AI-generated cover letters and resumes, enforcing these rules is nearly impossible. To combat AI-assisted applications, many recruiters are turning to AI-detection tools, but these systems are far from perfect. They often fail to reliably distinguish between human- and AI-written content.

Faced with this challenge, some companies are rethinking their hiring processes and shifting toward skills-based hiring. By testing real-world capabilities rather than focusing on job titles or degrees, employers hope to assess candidates more accurately and objectively. However, even skills tests are vulnerable to AI infiltration. Rostrum, a recruitment firm, discovered that candidates were using AI to complete written assessments, leading them to require in-office or video-supervised tests to ensure authenticity.

The widespread use of AI also risks deepening gender imbalances in the workplace. A 2024 study found that 50% of men had used AI in job applications over the past year, compared to only 37% of women. As a result, employers may receive more male applications, simply because men are using AI tools more frequently.

Ultimately, while AI makes it easier for applicants to mass-produce polished resumes, companies are rediscovering the value of human authenticity. By using diverse assessment methods—such as soft skills evaluations, in-person exercises, and motivation tests—employers can better identify the people behind the applications.

ZNEST’S TAKE
Key Takeaways

• Ineffectiveness of Job Boards: Only 1-2% of applicants from job boards get hired, despite 75% of applicants using them (LinkedIn, 2022).

• Hiring Process as an Arms Race: Companies adopted ATS systems in the mid-2000s to filter applicants based on keywords, often rejecting qualified candidates due to formatting issues or keyword mismatches.

• Flaws of Resumes in Hiring: Resumes have weak correlations with job success and fail to capture soft skills, with 55% of resumes containing inaccuracies.

• AI and the Irony of Resume-Based Hiring: AI is revealing the flaws of resumes, prompting companies to shift towards skills-based hiring and real-world assessments.

• Recalibrating Hiring Practices for the AI Age: Companies must adapt hiring practices to focus on skills and abilities rather than resumes, creating a more human-centric and equitable process.

Anyone who has looked for a job in the past couple of years anecdotally understands the futility of job boards. The statistics are just as bad. According to Jobvite’s 2023 Job Seeker Nation Report, only ~1% to 2% of applicants who apply through online job postings actually get hired. LinkedIn data (2022) shows that over 75% of applicants apply through job boards, but they account for only 15% of hires.

🚀 The Hiring Process as an Arms Race

The stark realities of job hunting has made it so the relationship between hiring companies and job applicants increasingly resembles an arms race, with both sides continuously adopting new tools and tactics to gain an edge.

The clearest example of this is the adoption of ATS (Applicant Tracking System) keyword filtering in the mid-2000s. As job applications moved online, more applicants were able to apply to a job than ever before. Companies responded by adopting tools to help them filter those applicants. However, those rudimentary filters focused on keywords much like search. According to a 2021 study, Applicant Tracking Systems filtered out 75% of resumes due to lack of keyword matches, even when candidates are qualified. To make matters worse, resume formatting inconsistencies or PDF parsing issues in ATS automatically disqualify applicants, regardless of qualifications.

Over the past ~20 years, that system has been refined but not fundamentally changed. Candidates applied to even more jobs and adjusted their resumes by “keyword stuffing” in an effort to beat the filter. Services like Jobscan also helped candidates in this endeavor. AI is only the next evolution of the race.

📚 What Academic Research Says About Resumes in Hiring

The modern resume is being used for far beyond their original purpose of listing qualifications. They are now used to gauge future job performance, screen for fit, measure skills, etc. Academic studies over the years have shown that traditional resumes are very bad at doing these things. Some key findings include:

• Resumes (based on experience and education) had a weak correlation with future job performance.

• Years of experience on a resume had little to no predictive value for job success.

• There are high amounts of unconscious bias during resume screenings.

• Resumes fail to capture soft skills (e.g., adaptability, problem-solving) which are strong predictors of job success.

• 55% of resumes contain some level of inaccuracy, making them unreliable.

🤖 AI Ironically Reveals the Flaws of Resume-Based Hiring

As AI streamlines the application process, exaggerates skills, and inflates total application numbers, companies are realizing that resumes are poor proxies for understanding an applicant. AI, often viewed as dehumanizing, is driving companies to focus on what candidates can do, not just what their resumes say. The challenge moving forward is how to modernize hiring for the AI age.

The issue is not whether or not to use technology, but how to adapt technology to the true problem—matching a candidate to a job based on what is actually required and the candidate’s true abilities. How do you match candidates based on skills, not job titles? How do you identify transferable skills from unconventional career paths?

These are significant challenges that will require a recalibration of decades old hiring practices. However, companies must learn to prioritize the human side of hiring, making the process more genuine, equitable, and human-centric through the use of diverse assessment methods.

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