Artificial intelligence may be quietly reshaping one of the most closely watched indicators of the U.S. economy: the monthly unemployment report.
Some labor experts say the growing use of AI-powered hiring tools — designed to screen and rank job applicants — may be preventing many qualified candidates from ever reaching a job interview, potentially affecting how the labor market appears in federal statistics.
The question is whether those invisible filters are helping create a gap between the number of people looking for work and the number of people who actually get the opportunity to compete for a job.
When the U.S. Labor Department released its February employment report, the numbers showed that the economy shed 92,000 jobs and the unemployment rate ticked up to 4.4%, bucking expectations that the labor market would remain resilient.
Some analysts believe part of the explanation may lie earlier in the hiring pipeline, where automated systems now review millions of job applications before a human recruiter ever sees them.
Across corporate America, AI-driven hiring platforms evaluate resumes, scan for keywords and assign scores to candidates. The systems are intended to help companies manage overwhelming volumes of applications, but critics say they may also filter out applicants who would otherwise have received at least an initial interview.
“It’s harder and harder for people to get a job,” said RedBalloon CEO Andrew Crapuchettes. “Basically what’s happening is you’re taking a very complex human being and whittling them down to a piece of paper we call a resume, and then AI is making decisions based on that.”
Today, nearly two-thirds of large companies use some form of AI to screen applicants, according to industry surveys. Many systems analyze employment histories, education credentials and specific keywords before ranking candidates. Applicants who score below certain thresholds may never advance to the next stage.
For job seekers, the process can feel opaque. Applications often disappear into online portals without feedback, leaving candidates unsure whether their rejection came from a recruiter or an algorithm.
That shift has already drawn scrutiny from regulators and the courts.
In 2018, Amazon abandoned an internal AI recruiting tool after discovering that it systematically downgraded resumes submitted by women. More recently, a federal lawsuit filed in 2023 — Mobley v. Workday — accused a major human resources software platform of using AI screening tools that discriminated against applicants based on race, age and disability.
The case sent shockwaves through the recruiting industry and highlighted the potential risks of allowing algorithms to play a central role in employment decisions.
New regulations in New York City, Illinois and Washington state require greater transparency and bias audits for automated hiring systems. Similar rules are being considered in the European Union.
Even when AI systems function as intended, critics say they may still reshape hiring in ways that narrow the field of candidates who reach interviews.
Traditional hiring practices allowed for a degree of human judgment. A recruiter might notice an unconventional career path, transferable skills or a promising candidate whose resume did not perfectly match a job description. Automated systems tend to reward exact matches between keywords and job postings.
That can leave qualified candidates stuck in a digital queue.
Some experts believe the disruption may prove temporary. As companies struggle to fill roles, they may eventually adjust how they use automated screening.
At the same time, businesses say AI hiring tools have become necessary. Large employers can receive tens of thousands of applications for a single role, making manual screening unrealistic. Automated systems promise efficiency, consistency and cost savings.
Supporters also argue that properly designed AI systems could eventually improve hiring by identifying talent and potential beyond what a resume alone reveals.
For many job seekers today, however, the immediate reality is simpler: the first interview may depend less on impressing a recruiter — and more on convincing an algorithm to pass them along.
“For millions of job applicants, often the biggest hurdle isn’t a lack of talent — it’s a digital filter that is blind to talent it hasn’t been programmed to ‘see,’” said attorney Gary Phelan, a partner at Hurwitz Sagarin & Slossberg LLC.
“We have entered a dangerous era where Applicant Tracking Systems (ATS) act as digital gatekeepers, hidden biases that may silently purge candidates based on age, race, gender or disability before a human ever sees their name.”
Phelan said the scale of artificial intelligence in hiring has grown rapidly. Nearly all Fortune 500 companies — about 99% — use AI tools or applicant tracking systems to screen and rank candidates, he wrote. About 87% of companies use AI somewhere in the recruiting process, and roughly three-quarters use automated systems to reject applicants without a human reviewing their materials.
Recent lawsuits, he said, illustrate the risks, including the Mobley v. Workday case, which alleges that AI screening systems may learn discriminatory patterns from historical hiring data.
If companies historically hired younger workers, Phelan wrote, algorithms may interpret youth as a signal of success and filter out older applicants using indirect clues such as graduation dates or years of experience.
He said employers cannot avoid responsibility simply because an outside vendor designed the technology. The Equal Employment Opportunity Commission has warned that companies may still be liable if AI tools they use produce discriminatory outcomes.
Additional litigation is emerging against AI hiring platforms, he noted, including a lawsuit accusing the company Eightfold AI of creating secret profiles on job applicants using scraped public data.
Phelan wrote that employers can reduce risks by conducting third-party bias audits, cleaning training data and ensuring human oversight in hiring decisions. At the same time, he said lawmakers are increasingly debating regulations governing AI systems used in employment and other high-stakes decisions.
For now, Phelan said, court challenges remain one of the primary ways workers can hold automated hiring systems accountable.
