A 2026 study from the Manpower Group reveals a troubling statistic: 72% of employers are facing challenges in locating the skilled talent they require. Ifedapo Adeleye, who leads the human resources management master's program at Georgetown University, shared insights that highlight a critical issue. While artificial intelligence is improving some operational efficiencies within human resources, it has not significantly expedited or enhanced the core tasks of identifying suitable candidates or streamlining the hiring timeline. Additionally, there is little evidence to suggest that organizations are better at retaining new hires. A Gallup survey reveals that 52% of American employees are either on the lookout for new job opportunities or actively seeking new positions, marking the highest level of job-seeking behavior since the surveys began in 2014.
One potential solution to this challenge could involve revisiting some traditional hiring methods, alongside establishing federal regulations that require employers to adopt more transparent and equitable evaluation practices.
The shortcomings of automated hiring systems have become increasingly apparent. According to Ifeoma Ajunwa, a law professor at Emory University and author of "The Quantified Worker: Law and Technology in the Modern Workplace," machine learning in the hiring process has been prevalent for over a decade, often before most individuals were considering the implications of AI. Ajunwa first recognized the pervasiveness of automated hiring technology while conducting interviews with formerly imprisoned individuals who had completed their sentences and were pursuing new job skills. Unfortunately, they found that automated systems were likely to disqualify them due to employment gaps or their forthrightness regarding their criminal backgrounds.
During the mid-2010s, numerous startups proposed that algorithmic hiring could offer a less biased and more efficient route. By 2011, more than 75% of job seekers were searching for employment online, which led to a deluge of applications that employers needed help managing. The situation has only escalated with the advent of ChatGPT in 2022, as new services like LazyApply and aiApply now allow candidates to customize their resumes and cover letters effortlessly. However, evidence suggests that machine learning has often perpetuated existing biases, complicating the process further for HR professionals by introducing issues such as fake applicants and dishonesty in skills assessments.
