Concerns arise from employers using AI employment tools

Applications of AI


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Blueprints

  • 74% of companies plan to hire AI within a year.
  • A third expects AI to run the entire recruitment process by 2026.
  • AI is most used for resume reviews, ratings, and interviews.
  • Experts warn of risks: bias, limited human surveillance, and litigation.

Oklahoma City – Job seekers may be shocked to learn that the role of artificial intelligence in employment is expanding to running shows by throwing inadequate resumes.

In August, Resume.org looked into 1,399 full-time U.S. workers into corporate practices to understand how AI is transforming their recruitment process.

Almost three-quarters of businesses (74%) plan to increase the use of AI in employment for the next 12 months, with a third likely AI to carry out the entire employment process by the end of 2026, the study found.

“These predictions are realistic given current adoption trends,” Kara Dennison, head of Advising, said in the report.

“For job seekers, this shift could mean faster application processes, more consistent assessments and greater reliance on digital assessments,” Dennison said. “But it could also reduce human interactions, limit opportunities to build trust and increase the importance of aligning applications to AI-driven screening standards.”

Applicants who understand how AI tools evaluate resumes, skills and interviews will have an advantage, but others may face more rejections without understanding why, she said.

According to the report, AI is already a standard part of the hiring process, with 57% of companies using it.

This study shows that AI is most used in resume reviews (79%), candidate ratings (66%), and researcher studies (63%). The next best uses are for candidate communication and onboarding, both of which are around 40%.

“In general, businesses use AI to scan their resumes and draft performance reviews, all of which should be done with caution,” says Phoebe Barber, associate prosecutor at Philips Muller in Oklahoma City.

“If clients use AI in employment or HR capabilities, human monitoring is absolutely essential,” Barber said.

Because AI relies on historical data, we can see that “engineers” are primarily associated with men and “nurses” are related to women. It could discriminate when sorting your resume by rejecting qualified candidates that don't fit that description, Barber said.

Employers are responsible for unintended consequences. From now on, job seekers who advocate for the use of AI in employment do not need to prove intentional discrimination, she said.

The survey shows that among companies using AI, 35% reject candidates at every stage of the hiring process based on AI recommendations, while only 26% advocate human surveillance for all rejections.

Over a third (34%) of companies currently using AI use it in their interviews. Rely on AI to analyze candidate languages ​​(66%), transcribe interviews (65%), and evaluate tone, language, or body language (59%).

Half of them allow AI to conduct interviews directly, with only seven in ten people constantly holding human surveillance.

AI is dangerous because candidates may interpret speech impairments or tensions because they are not eligible, Barber said.

Phillips Murrah recommends that businesses adopt AI policies that cover acceptable and prohibited use in both employment and all functions.

Barber said audits showing how AI is used and how the results are used are an important safeguard.

“Companies should open up with candidates about the role of AI in employment to build trust, improve candidate experience and meet evolving compliance standards,” Dennison said in the report. “This means clearly explaining where and how AI is used, whether it is to make recommendations or rejections, the level of human surveillance, and what data is being collected.”

Of the companies using AI in their employment processes, 74% said they improved the quality of their employment. Still, many companies are cautious about AI restrictions. The biggest concern is that eligible candidates (57%) can be screened and biases (50%) can be introduced.



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