From Resumes to Robots: How AI is Shaping the Future of Recruitment
Is getting that offer letter going to become easier or even harder than it already is?
It was in the year 1997 that Steven Hankin of McKinsey & Company crafted the phrase ‘War for Talent’. While speaking about the said talent wars, Hankin referred to the rise in difficulty in acquiring candidates that propel the growth of the company by rendering a positive return on investment and retaining such employees that already assist the firm in maintaining its profitability.
Nearly three decades have passed since the coinage of the phrase and the “war” has only intensified over the years. From an economic perspective, the talent wars directly correspond with the supply and demand cycle.
To clarify, when the demand for quality labor or manpower exceeds its supply, firms would participate in intense cold battles to secure the best of the talent pool available. However, when the supply exceeds the demand, the competition amongst firms would abate.
Of course, as one would anticipate, the merging of artificial intelligence with the current recruitment processes is bound to spice things up a bit. Specifically, if a recent research paper by Black & Van Esch (2021) is taken into consideration, the integration of AI is expected to intensify the competition amongst firms to secure top talent irrespective of the existing state of demand and supply of personnel.
There are a multitude of reasons as to why such a situation may emerge.
Firstly, AI is capable of identifying top talent more effectively by enhancing the screening process given its ability to quickly sift through a large volume of applications that big companies are likely to receive.
Algorithms that match candidates' skills and experience accurately with job requirements have already become mainstream. Hence, the stress on utilizing specific keywords in your resumes in order to pass through the applicant tracking systems (ATS) that are becoming increasingly AI-driven.
Secondly, AI tools can identify passive candidates who are not actively looking for jobs but may be a perfect fit for a role. When AI is used to reach out to such candidates, companies engage in proactive recruitment which increases the pool of potential hires along with the competition among employers.
Thirdly, by gaining an in-depth understanding of the candidates’ experience and profile, AI can provide a more personalized and engaging experience, making the company more attractive to top talent. This serves as a more subtle form of employer branding, which, of course, we will talk about in more detail in another article.
Lastly, bringing in the big guns, one of the big roles that AI would and is fulfilling is making use of data to determine trends and patterns in recruitment for workforce planning. Further, AI can utilize predictive analytics to identify which candidates are likely to be high performers, thus intensifying the focus on securing these candidates.
Proactive Recruitment
I want to talk about proactive recruitment in a little more detail. Before artificial intelligence-driven methods became mainstream, the only way companies could access the huge database of passive candidates was through executive search firms.
As you would expect, these firms did not shy away from charging hefty prices for their rather exclusive services. With such high costs, companies utilized passive candidate search facilities only occasionally.
However, now that AI-powered software services have become available at large all the while costing only a fraction of the expenses that were previously being incurred, companies are able to forgo the usage of the services that search firms offer.
Big data from social platforms such as Facebook (sparingly) and LinkedIn (primarily) is accessible for pennies and allows companies to create their own customized databases of passive candidates that fulfill the firms’ unique needs.
While the scope of recruitment has certainly widened given the newfound capabilities of AI, talent wars have exacerbated simultaneously.
Why?
Because employee replacement results in an additional demand for top talent that goes beyond the existing demand and supply chain driven by simple economic factors.
Moreover, it goes without saying that replacing an employee is a costly affair, so much so that it can put a dent in the meager budget that HR departments are granted.
To quantify, as per data from Gallup, replacing an employee may cost anywhere from 50% to 200% of the employee’s salary. So if you are paying an employee 100k a year, replacing them may cost you anywhere from 50k to 200k on top of the regular salary that you would anyway be paying to the new employee.
And not just that, the additional, albeit temporary, burden that is put upon the existing employees as they scramble to carry the workload of the employee who quit makes your company considerably less attractive to your existing employees, potentially resulting in a vicious cycle of high attrition.
While it would seem that I have digressed from the primary topic of discussion, the point that I am trying to make here is that utilizing AI for recruitment is essential and you better believe that your competition is already integrating AI into their recruitment processes.
Sticking to the traditional methods of recruitment will only result in a Nokia-like fate.
Change must be embraced; there is no circumventing it.
Hyper-personalization
Now that AI has gathered significant attention and the Metaverse is in the picture, hyper-personalization is no longer just a dream. While hyper-personalization in recruitment is not yet a reality, it is a highly plausible prospect.
Traditional tools are entirely inadequate and cannot offer even a sliver of personalized experience for candidates during the hiring process. After all, it is impossible for a human recruiter to learn about each candidate on an individual basis and then craft tailored messages.
If a recruiter were to take on such an approach, a single hire would take months to be finalized, not to mention, the recruiter would be burnt out before you knew it.
Bias-free
It is pretty self-explanatory that AI is unlikely to care about a candidate’s pretty privilege or if they have an uncle who is a member of the ruling political party or if their mother is a team lead in a sister company.
All those biases and prejudices that plague the human mind elude the artificial one. When all the biases are removed from the evaluation process, only a candidate’s fit for the role would determine their probability of getting hired.
Such bias-free hiring would also help propel diversity and inclusion initiatives in an organization. This is not to say that AI would make perfect decisions and hire the best candidate for the role.
Of course, there might be instances where AI overlooks a certain candidate who is better for the role because their interviewing skills are not up to the mark. Plus, when diversity and inclusion metrics are considered, AI may, in fact, display biased behavior if the data it is trained upon is already biased.
For example, if historically only people of certain ethnic groups are hired within a firm, AI may take that as an instruction to continue the trend. To take a real life instance, in 2018, Amazon abandoned its hiring tool when it was discovered to be biased against women as the data the tool was trained on consisted primarily of resumes of men sent in for technical roles.
For these reasons, recruitment can never be an entirely AI-driven process, and the human touch must always remain.
Virtual Virtual Interviews
No, there isn’t a typing error in the sub-heading. What I mean by virtual virtual interviews is the fact that the future is not only about remote, online interviews but also about interviews taken by bots.
HireVue, a bot-based recruitment company, is already making headway in this domain (I will discuss HireVue in detail in a separate article). When such software is used, the candidate’s initial interaction is with the computer program that usually presents itself as a humanoid.
The perks include an increase in the time-effectiveness of the recruitment process along with arguably bias-free hiring. There are downfalls too, however.
For some candidates, such an experience of being interviewed by a bot might be unnerving as it is likely to be an experience they have never had before. Many others would doubt the capability of AI in accurately evaluating their responses and determining fit.
Conclusively, at least at this point, while the pros for bot-based hiring are limited, such recruitment is nonetheless expected to become the standard in the near future. Hopefully, by then, the pros would outweigh the cons.
And that wraps up the latest edition of The Channel. Hopefully, you found reading the article worthwhile. What are your thoughts on AI-driven hiring? Have you experienced it yourself yet? Feel free to share your thoughts in the comments!
Until next time,
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