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For decades, talent acquisition has been hindered by legacy processes designed for a bygone era of work. Outdated infrastructure and piecemeal system updates have only added friction, leaving recruiters juggling disconnected platforms while candidates endure confusing, drawn-out hiring experiences. Traditional TA systems may track applicants, but they rarely optimize the full talent lifecycle. They often lack interoperability, provide limited analytics for strategic decision-making and fail to meet modern candidates’ expectations for seamless, digital experiences.
The result: wasted recruiter effort, frustrated candidates and missed opportunities to hire top talent. In today’s fast-moving labor market, such inefficiencies aren’t just inconvenient; they’re a direct drag on business performance. Over the past few months, The Josh Bersin Company has been exploring this issue, prompted by data showing that only 17% of applicants reached the interview stage last year, while 60% abandoned their applications altogether due to slow, outdated processes.
We need a better way to do this, and artificial intelligence, both generative and machine learning, offers a clear alternative. It’s one that a growing number of TA teams are turning to, and our discussions with multiple hiring teams show AI adoption is accelerating fast, underlining how quickly HR and TA teams are embracing AI-driven
