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Future of Hiring With Talent-Aquisition Technology

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By William Vogeler, Esq. on April 11, 2019 12:01 PM

Some day, job applicants will sit down across a desk from a robot -- a real robot, not a humorless person who just acts like one.

In some ways, it is already happening. Artificial intelligence is working on job applications, screening candidates, and even matching personality profiles. Smart robots are so good it can stun hiring managers.

That's why more companies are turning to talent-acquisition technology. Job recruiters are already using AI, they just don't want the robots to take their jobs.

AI at Work

Entreprenuer said it would be like this: big data, intelligent platforms, and AI are "a great solution to the cost issue in hiring." It's not about finding another worker, it's about finding the perfect fit for employee and employer.

"This kind of synergistic relationship is the ultimate recruitment goal," wrote Brian Hughes. "It's especially critical in small companies and startups where every person has a huge impact on the business's success."

Recruiters have found a sweet spot with companies like Search Technologies, he said. It uses big data by processing document-to-document word match, saving recruiters time in delivering the best candidates. Leader Theory uses algorithms to find leadership applicants and to evaluate existing internal talent. Hughes says the process ensures applicants are "the best fit" for the job and company culture.

In addition to producing intelligent and fast results, AI offers the benefit of saving money in recruitment costs. To find a replacement for a departing employee, The Society for Human & Resource Management says, it costs about half that person's annual salary.

Frontiers Ahead

A year ago, it was an open question whether AI could revolutionize the hiring process. Now, it's hardly a question. However, there are still frontiers ahead. Implicit bias, for example, is a problem in employment and many other endeavors. It will take more intelligence from humans to deal with bias in hiring.

Robots don't really have that problem.

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