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When Machines Hire Man



The process of talent acquisition as a corporate function has undergone evolution and even revolution since the beginning of time. In its earliest days, hiring decisions used to be largely based on personal recommendations and walk- in interviews. These were subsequently replaced by newspaper advertisements for job postings and mailed job applications. The advent of the digital age at the turn of the century has further changed the talent acquisition and recruitment landscape. While the processes have remained intact, they have mostly migrated online. Job requirements are posted on job boards and applications are received via the same platform. And, more importantly, the entire recruiting/hiring process is being managed through an elaborate Applicant Tracking System (ATS). 


Increasingly, recruiters are also expanding their talent search beyond traditional job boards such as to include social media like LinkedIn. This is especially prevalent for job roles that require deep skills – because it is simply easier to hunt for what is needed than to wait for a suitable applicant to come along. 


Seemingly, one might wonder if going to such an extent is justi able. It de nitely is. The cost of a wrong hire is expensive, not just in terms of dollars spent but also the wasted time and investment. To make matters worse, losing a good candidate – either because of internal bureaucracy or an inexperienced recruiter – may also mean that this talent will be working for the competition. Again, something expensive but hard to quantify in dollar terms. 


That is why recruiters are now capitalising on AI’s capacity to adapt and learn from past behaviours to fast track the talent acquisition process as well as score better hiring outcomes. 




Thanks to AI, the search for potential candidates is no longer just a waiting game or an endless hunting quest. There are now software that can crawl through potential and suitably quali ed candidates’ social media pro les and interactions to assess their suitability for job roles. Recommendation is then made to the prospective hire to lead him/her to the company’s career site, and possibly put in a job application. 




In the present day context, the selection of one candidate over another is often clouded by personal biases of the recruitment manager. Therefore, rather than hiring for job t and suitability, candidates could be hired for reasons ranging from their chemistry with the hiring manager to their outward appearance vis-à-vis that of other interviewees. However, with the intervention of AI and Deep Learning based software, candidates can now be assessed more objectively by taking into account their existing performance in the same role as well as the suitability of their personal attributes to the prevailing corporate culture. 




It is not unusual for Talent Acquisition (TA) Specialists to be unfamiliar with the job scopes they are hiring for and rely on “Key Word Searches” to identify suitable candidates. This is a hit-or-miss approach because research has shown that more than 30% of suitably quali ed candidates do not use keywords present in the job description. With a human TA Specialist, many of these potentially good candidates will have been ltered out. But with AI and its natural language processing capability, resumes are now better “understood” and matched with job requirements. Resultantly, TA Specialists can be more certain that they are not missing out on suitable candidates as well as focus their attention on ensuring a smooth selection process. 




Unknowingly, many opportunities are lost each time a hirer makes his decision on the selected candidates. The unsuitability of one candidate for a particular role does not necessarily mean that he/she is unsuited for the company. In fact, they could very well t another role perfectly. But, in the traditional hiring process, these good candidates would be missed because they are suitable for job roles they did not apply for. The AI software intelligently “studies” the resumes of candidates and ranks their suitability for the various roles available, giving the jobseekers and the hiring companies a second and, even, a third chance to “ nd” each other. 


The influence  of AI on talent acquisition and recruitment process continues to evolve today. In a time where mid-career professionals with deep experience are being displaced, AI empowered software brings hopes for better job matches and more effective workforce utilisation. So don’t be surprised when in the foreseeable future, a machine can help you land your next job! 





Teng Cheong is a seasoned IT professional who headed up local and regional operations of several IT MNCs before founding his own search firm called BetterIDEAS. His company focuses on using seasoned IT professionals to hire IT talent for companies because he believes that "the best way to hire a professional is through an even more seasoned professional in the same field". 



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