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AI set to revolutionize recruitment: Hays

Artificial intelligence (AI) is set to change the way the recruitment industry and organizations search for and acquire talent, according to recruiting experts Hays.

Automated technology can analyze the mountains of data that exist within an organization and the wider job market, translating it into easily digestible formats. According to Alistair Cox, CEO of Hays, this will help humans make better recruitment decisions.

Cox sees three key areas of recruitment that AI will revolutionize:

AI will bring more efficient and fairer candidate screening

“One simple job ad can elicit tens of thousands of responses, many of which may be wholly inappropriate applications, yet all must be screened in order to find the real stars,” said Cox.

With the aid of AI, time consuming areas of recruitment, such as CV screening, drafting job descriptions and communicating with candidates, could instead take seconds. This will free up time to focus on the human aspect of recruitment and offer a more personal service to clients and candidates.

Hays has already taken its first steps in harnessing the power of AI with an external partner, Cox states “This platform has certainly accelerated the shortlisting process for us, and it also enables our recruitment consultants to concentrate on assessing the individual candidates outlined by the technology to be the best fit for the role in hand, rather than pouring over a wider pool of hundreds of thousands who may not be suitable.”

AI will ensure a better candidate fit

The main cause of an unsuccessful hire is a poor cultural fit between employee and organization. AI has the potential to overcome this. Online job boards already use algorithms to match their community of job seekers with available roles. For example, a LinkedIn job posting will rank the suitability of candidates by utilizing the available information on their profile.

As AI develops, these algorithms will not only take technical capabilities into account but will become more sophisticated and analyze a candidate’s likely fit to the organization.

However, the human element will remain a key part of the process. As Cox explained, “It remains incredibly difficult for any machine to analyze the soft skills that remain so crucial to modern business. I’m yet to see an algorithm that can read things like humor, temperament or enthusiasm as effectively as a person can. And let’s not forget that ultimately human oversight is still required to compile criteria – I certainly wouldn’t want a machine deciding the persona of my business, and I don’t think it would do a particularly good job yet.”

AI will help safeguard future talent pipelines

AI has the potential to improve employee retention and development. The retail sector has been harnessing customer data successfully for years, so they are able to target their customers with offers and rewards tailored to the individual. Cox expects employers to follow suit, offering a more personalized approach to incentives. It’s also possible that AI could inform managers of when they are at risk of losing a member of their team, giving them ample time to intervene.

There is also the potential to supplement proactive human planning. “An organization’s talent flow is essentially another data spread that a computer can analyze to spot upcoming trends, either assessing when future revenue growth will require additional staff, or analyzing calendar patterns to identify which time of year employees are most likely to depart, for example,” Cox said.

While these developments in AI will make the recruitment process far more efficient, allowing hiring managers to focus on higher value tasks, Alistair stresses the importance of not losing the human touch.

“Today people do business with people and I hope that never changes. Despite the excitement and fears around the rise of AI, talent management largely remains a contact sport, where gut feeling, grounded in thousands of tiny facets of human experience which are never captured as data, plays just as strong a role as hard data.”

First published in SMBWorld Asia