A study on the impact of artificial intelligence on talent sourcing

Varun Chand Hemachandran, Kurakula Arun Kumar, Syarul Azlina Sikanda, Seema Sabharwal, Sivaprakasam Arun Kumar


Talent sourcing is one of the most effective mechanisms to engage with the talent pool and convert a candidate into an applicant. Today, machine learning has emerged as a trend to assist employers in addressing recruitment challeng-es with the help of tools such as neuro-linguistic programming (NLP) and automated assessments. 80% of the executives strongly believe deep learning makes candidate screening highly efficient. Including current start-ups globally, only 15% use artificial intelligence (AI) and are expected to increase by 31%. The study focused on the impact of AI in recruitment process. There are a few metrics, such as application completion rate, number of candidates per filled position, cost per hire, and so on. Here we would like to analyze the impact of using AI in various phases of hiring in the organization.


Artificial intelligence; Candidate evaluation; Machine learning; Neuro-linguistic programming; Predictive analytics; Screening;

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DOI: http://doi.org/10.11591/ijai.v13.i1.pp1-8


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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938 
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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