A study on the impact of artificial intelligence on talent sourcing

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 challenges with the help of tools such as neuro-linguistic programming (NLP)...

全面介紹

書目詳細資料
發表在:IAES International Journal of Artificial Intelligence
主要作者: Hemachandran V.C.; Kumar K.A.; Sikandar S.A.; Sabharwal S.; Kumar S.A.
格式: Article
語言:English
出版: Institute of Advanced Engineering and Science 2024
在線閱讀:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178164009&doi=10.11591%2fijai.v13.i1.pp1-8&partnerID=40&md5=01d7e561f0846f3fb88f80dedbd04ec6
實物特徵
總結: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 challenges 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. © 2024, Institute of Advanced Engineering and Science. All rights reserved.
ISSN:20894872
DOI:10.11591/ijai.v13.i1.pp1-8