# AI Use in the Job Market Is Creating an Infinite Doom Loop

> Job seekers and employers are increasingly relying on AI tools, sparking a vicious cycle of distrust and inefficiency that benefits neither side in the current economic landscape.

**Type:** article · **Category:** AI · **Published:** 2026-09-04 · **Source:** TrendKia
**Canonical:** https://trendkia.com/en/ai/ai-use-in-the-job-market-is-creating-an-infinite-doom-loop-27680 · **Language:** English
**Tags:** AI job market, Applicant Tracking System, career search, recruitment process, artificial intelligence, job hunting

In today's employment market, job seekers and companies are locked into an escalating technological arms race. Beggs, a data scientist and active job seeker, received feedback from an online matching system that compares job descriptions directly against applicant materials. While Jobscan stands as the most prominent of these evaluation tools, Beggs did not specify which particular platform she tested.

 

## The Myth and Reality of ATS Filtering
 Applications like Jobscan operate on the underlying assumption that hiring committees deploy artificial intelligence to automatically sort, rate, and rank candidates inside their applicant tracking system. Under this common belief, only the top ten to twenty percent of applicants ever receive consideration, while the remaining eighty percent vanish into obscurity. To secure a spot on the shortlist, candidates feel compelled to optimize their resumes and cover letters with precise keyword density tailored to satisfy the automated gatekeeper.

 The core difficulty is that this widespread premise simply does not hold true universally. While automated candidate ranking certainly occurs within certain enterprises, other institutions continue to manage recruitment entirely through human oversight from the very beginning to the final offer.

 

## Understanding the Applicant Tracking System
 At its foundational level, an applicant tracking system gathers submissions, assists hiring panels with reviews, and monitors candidates throughout the interview and selection pipeline. Some advanced software packages offer expanded capabilities, ranging from onboarding administration to automated artificial intelligence screening interviews.

 Daniel Chait, chief executive officer of the ATS provider Greenhouse, points out that considerable folklore surrounds these technologies, particularly from the perspective of job seekers. No two tracking systems operate identically, and the underlying software evolves rapidly. Whether a specific system incorporates artificial intelligence depends entirely on the exact product version and the specific feature tiers a hiring team chooses to purchase and deploy.

 Regardless of the technical reality, as long as applicants remain convinced that artificial intelligence dictates their fate, they will continue attempting to outsmart the algorithms using their own automated tools.

 

## Economic Pressures and Market Realities
 Surrendering the outcome of a career search to software promising optimization for an ATS remains a precarious gamble. One recruiter notably demonstrated that even with exceptionally poor Jobscan ratings, she still secured a dozen interviews and a formal job offer. Furthermore, services like Jobscan charge anywhere from thirty to fifty dollars per month, meaning the platform lacks any strong commercial incentive to help users exit the job market permanently.

 Operating within a sluggish economic environment characterized by low hiring rates compounds these frustrations significantly. Open job listings remain scarce across many sectors, while scams and ghost job postings have grown prevalent enough to prompt several state governments to consider drafting new regulatory legislation.

 Both employment candidates and corporate recruiters report a severe breakdown in mutual trust. Job seekers sink countless hours into applications only to encounter absolute silence, turning the submission process into an opaque black box.

 Conversely, employers explain that they receive hundreds of nearly identical submissions, prompting them to feed the influx into automated rating software in a desperate bid to achieve quick differentiation among candidates.

 Chait describes the current environment as an artificial intelligence doom loop, noting that both sides face distinct dilemmas and deploy automated solutions that ultimately exacerbate the underlying friction. As more participants adopt these methods, the overall utility diminishes for everyone involved.

 

## Corporate Perspectives and Human Review
 Conversations with dozens of recruiters, human resources managers, and independent business owners reveal a stark division in hiring philosophies. Some admit to utilizing automated candidate scoring, while others insist they completely avoid it. This divergence bears no direct relation to organizational scale or the sheer volume of incoming applications, appearing instead to stem from foundational corporate culture.

 Kim Jones, vice president of human resources at Toshiba, emphasizes that human reviewers evaluate every single application submitted to their organization. While she holds no objection to applicants utilizing artificial intelligence to polish their application materials, she notes that it offers no genuine advantage in bypassing the tracking system. Candidate elimination is determined primarily by core job requirements, compensation expectations, and administrative factors such as prior employment history with the company.

 Where Jones has observed unwanted artificial intelligence deployment is during the actual interview phase, noting instances where unnatural pauses and typing sounds precede overly verbose responses from candidates.

 Another organization favoring human-led recruitment is Doist, a small, fully remote enterprise operating across international borders, which naturally generates massive applicant pools whenever a position opens.

 Nadia Vatalidis, head of people at Doist, conducted an internal experiment to evaluate whether tracking system algorithms could successfully replicate their hiring decisions. Her team fed job descriptions and archived candidate materials from previously filled roles into an automated ranking system to test output accuracy. The experiment revealed that in two tested instances, the individuals ultimately hired and thriving after six months did not even make the automated shortlist.

 

## Job Seekers Fighting Back With Technology
 When James Jacobsen initiated his career search five months ago, the time commitment rivaled a full-time occupation. As a professional designer, he understands that machines cannot replicate human creativity, yet he actively experiments with automation for specific operational tasks. He utilized Claude and ChatGPT to refine his resume and align his credentials with job postings, though these tweaks yielded little measurable progress.

 Pivoting away from document optimization, Jacobsen began instructing Claude to systematically aggregate, analyze, and track job listings from top to bottom. He developed an intricate scoring rubric factoring in role type, seniority levels, and variable salary thresholds depending on remote or hybrid arrangements. His custom assistant highlighted optimal openings and maintained detailed rejection notes to prevent wasted effort if identical roles were reposted weeks later.

 He effectively constructed the inverse of a corporate tracking system, managing his entire search pipeline independently.

 Jacobsen extended this approach by having language models critique his professional portfolio, prompting a grueling six-hour overhaul. Two days following the update, a prospective employer reached out, though the lead ultimately did not convert into an offer.

 Chait notes that candidates like Jacobsen are exhausting themselves trying to outwork a broken paradigm. Spraying applications across the internet no longer functions as an effective strategy, and both candidates and employers remain deeply dissatisfied with current market mechanisms.

 Chait advises job seekers to invest time in researching specific organizations of interest rather than relying solely on high-profile corporate names. Toshiba's Kim Jones reinforces this sentiment, noting that physical cover letters are now exceedingly rare and immediately help an applicant stand out. Traditional networking remains an invaluable asset in navigating the modern employment landscape.

 Ultimately, Chait offers a comforting reassurance to frustrated candidates, reminding them that the systemic friction stems from broken infrastructure rather than personal shortcomings.

## What this means for you
The widespread adoption of automated screening and artificial intelligence in recruitment directly impacts the millions of professionals navigating today's competitive employment landscape.

- **Across India:** Job seekers should look beyond automated online portals and prioritize direct professional networking and targeted company research.

- **Resume Optimization:** Stuffing resumes and cover letters with automated keywords no longer guarantees interview shortlists, as human reviewers still dominate many hiring workflows.

- **Financial Costs:** Spending thirty to fifty dollars monthly on optimization subscriptions yields diminishing returns compared to investing that time into direct portfolio enhancement.

- **Systemic Strain:** Scarce job postings and ghost listings create widespread frustration, turning the modern application process into an exhausting, opaque ordeal.

## Questions & Answers

### 1. What is an ATS?
An applicant tracking system is software used by hiring organizations to collect applications, manage reviews, and track candidates through the hiring pipeline.

### 2. Do all companies use AI candidate ranking?
No, while some organizations utilize automated scoring, others rely entirely on human review from start to finish.

### 3. How much does Jobscan cost?
Jobscan typically charges between thirty and fifty dollars per month for its optimization services.

### 4. How does Toshiba handle job applications?
Toshiba relies on human reviewers to evaluate every single application rather than depending on automated tracking system filters.

### 5. How did James Jacobsen use AI in his job search?
James Jacobsen used Claude and ChatGPT to aggregate job listings, build a tracking system, and critique his professional portfolio.

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