Half of job Seekers get rejected by AI without a word

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New data show how AI hiring practices are changing job seeker behavior.

Job seekers used to get a rejection email. Now, many get nothing at all. A survey of 1,066 US job seekers conducted in April 2026 found that 50.5% had been turned down without any human feedback in the past year, and most of them believed a machine made that decision. Some described unusual feedback from screening tools, including comments about eye contact or being told their pauses sounded unnatural.

The pattern points to a bigger change in how companies screen applicants and how workers respond to a job market that feels less predictable with each passing month. For many candidates, silence has replaced the rejection letter, and that silence is starting to shape how people plan their careers and how they think about income stability.

According to Enhancv’s research on AI hiring statistics, the silence is only part of the problem. Candidates also don’t know when AI enters the process, and that lack of disclosure is changing how people plan their careers.

An increasingly automated process

The survey findings portray recruitment as an increasingly automated process in which applicants may have limited contact with the people making hiring decisions. Among respondents who received a rejection without feedback, nearly two-thirds attributed the outcome to AI, compared with a much smaller proportion who believed a person made the decision.

The experience was particularly common among younger applicants. It also influenced whether some candidates continued with the recruitment process. Nearly one-third said they had abandoned an application or interview after encountering a one-way AI screening, suggesting that automation can affect not only how employers evaluate applicants but also whether applicants remain engaged.

Limited visibility for applicants

As automated screening has expanded, communication about its use has not necessarily kept pace. Although several states have introduced disclosure requirements governing AI in hiring, fewer than 1 in 10 respondents said an employer had clearly explained that the technology would be used. More than two-thirds recalled receiving no disclosure.

This limited visibility has contributed to broader questions about how automated tools assess candidates. Almost half of those surveyed believed the technology could treat applicants differently based on characteristics such as age, race, gender or background. The findings do not establish that particular tools produced discriminatory outcomes, but they illustrate the concerns that can arise when applicants do not understand how their responses are being evaluated.

From career path to income portfolio

The uncertainty extends past the application stage. Enhancv’s separate research on overemployment found that nearly 80% of professionals who hold more than one job view the second income as protection against layoffs. Taken together, the studies suggest that changes in recruitment are unfolding alongside a wider reassessment of employment stability.

Holding multiple jobs is also not limited to remote technology workers, despite its frequent association with that group. More than half of the professionals surveyed said they worked primarily in an office, while respondents represented fields including education, healthcare, and operations.

The results reflect a shift in how some professionals approach employment. Rather than treating one position as their sole source of long-term stability, they may distribute their time and earnings across multiple roles. In this context, additional work functions less as an unconventional career choice and more as a form of income diversification.

The cost of silence

Automated hiring and overemployment may appear to be separate developments, but both reflect uncertainty about the relationship between companies and workers. Employers are using technology to process applications at scale, while some professionals are seeking additional sources of income to reduce their reliance on a single position.

The survey also indicates that communication can influence how candidates respond to automated recruitment. Applicants who encounter unexplained decisions may withdraw from the process, leaving employers with a smaller pool of engaged candidates. A lack of information can therefore shape the hiring experience even when the underlying screening technology operates as intended.

The data suggest professionals are not waiting for greater certainty. Some are changing how they approach applications, interviews and sources of income as automated screening becomes more common. Meanwhile, employers face growing scrutiny over when AI enters the recruitment process and how clearly that involvement is communicated. The next stage of AI hiring may therefore be defined not only by what the technology can evaluate, but by how visible its role becomes to the people being evaluated.