A job seeker checks their inbox once more on a dreary Tuesday morning in a tiny apartment that is primarily illuminated by laptop light. Nothing. The coffee is cold now. The email tab remains obstinately quiet. Five hundred applications were submitted. No interviews.
It’s difficult to ignore how commonplace this has become.
Nowadays, looking for a job doesn’t feel like a conversation. It has the feel of an upload.
An Applicant Tracking System is the software that sits behind almost every corporate careers page. It silently scans resumes in milliseconds, parses keywords, assigns scores, and eliminates the majority of them before a human eye ever looks at a single sentence. According to studies, these systems automatically reject about 75% of applications, leaving candidates to wonder what went wrong when, in fact, no one ever made a judgment.
| Category | Details |
|---|---|
| Technology | Applicant Tracking System (ATS) |
| Purpose | Filters resumes before human review |
| Estimated Filtering Rate | Up to 75% of resumes rejected automatically |
| Average Applications per Job | Around 250 applicants |
| Average Recruiter Review Time | About 6 seconds per resume |
| Common Platforms | LinkedIn, Workday |
| Problem | Qualified candidates often rejected before human review |
| Reference | https://www.linkedin.com |
Being turned away by something that doesn’t even comprehend you is unnerving.
Twenty years ago, the volume of applications that recruiters now have to deal with while working remotely from kitchen tables or in open-plan offices would have been unthinkable. One hiring manager reported that after posting a job, 300 resumes were received in two days, the majority of which arrived overnight. The resumes were created and submitted more quickly than any human could possibly write them. It’s possible that automation has sparked an odd arms race in which employers are using AI to reject applications more quickly and applicants are using AI to apply more quickly.
Evaluation has been replaced by speed.
Applications are now simple thanks to websites like LinkedIn. A resume can be submitted in seconds with just one click. However, there are drawbacks to that convenience. Volume explodes when the application becomes frictionless. Filtering also becomes brutal when volume erupts.
It seems as though effort itself has become invisible as we watch this happen.
Once a meticulous account of a person’s professional life, a resume now consists of data points such as job titles, formatting, and keywords. Even after passing automated filters, many resumes receive less than six seconds of review time, as recruiters privately acknowledge. Half a minute. It’s hardly enough to get a name registered.
It calls into question merit in an awkward way.
Theoretically, AI filtering increases productivity by assisting businesses in rapidly identifying competent applicants. In actuality, it’s still unclear if these systems reward skill or just knowledge of algorithm-friendly language. In an effort to please software rather than people, candidates now spend hours customizing resumes to fit job descriptions and adding keywords.
The act of tailoring your life story to a machine has a subtly dehumanizing quality.
As AI tools enable candidates to instantly create polished resumes, the issue has gotten worse. Applications that appear impressive but feel oddly interchangeable, with similar phrases and structure, are reported by recruiters. Because of this uniformity, it becomes more difficult to discern between automated polish and real experience, leading to a greater reliance on filtering tools that might reject qualified applicants whose resumes don’t follow predetermined patterns.
Paradoxically, AI might be resolving an issue that it exacerbated.
A group of jobless software engineers sit in near silence in a downtown co-working space, looking at nothing and occasionally sighing as they work through job boards. They have impressive resumes. They have a genuine experience. However, they believe an unseen force is preventing them.
The system’s ability to adapt is still unknown.
Businesses insist that hiring decisions are still made by humans. In a technical sense, that is accurate. However, the majority of applicants are already gone by the time a resume reaches a person. The algorithm has made its voice heard.
Some job searchers have started to completely forgo traditional applications in favor of networking, direct outreach, and referrals. These methods seem slower, older, and strangely more human. They need discussion, not acquiescence.
Additionally, dialogue can still be effective at times.
