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)...
Published in: | IAES International Journal of Artificial Intelligence |
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Institute of Advanced Engineering and Science
2024
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2-s2.0-85178164009 Hemachandran V.C.; Kumar K.A.; Sikandar S.A.; Sabharwal S.; Kumar S.A. A study on the impact of artificial intelligence on talent sourcing 2024 IAES International Journal of Artificial Intelligence 13 1 10.11591/ijai.v13.i1.pp1-8 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178164009&doi=10.11591%2fijai.v13.i1.pp1-8&partnerID=40&md5=01d7e561f0846f3fb88f80dedbd04ec6 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. Institute of Advanced Engineering and Science 20894872 English Article All Open Access; Gold Open Access |
author |
Hemachandran V.C.; Kumar K.A.; Sikandar S.A.; Sabharwal S.; Kumar S.A. |
spellingShingle |
Hemachandran V.C.; Kumar K.A.; Sikandar S.A.; Sabharwal S.; Kumar S.A. A study on the impact of artificial intelligence on talent sourcing |
author_facet |
Hemachandran V.C.; Kumar K.A.; Sikandar S.A.; Sabharwal S.; Kumar S.A. |
author_sort |
Hemachandran V.C.; Kumar K.A.; Sikandar S.A.; Sabharwal S.; Kumar S.A. |
title |
A study on the impact of artificial intelligence on talent sourcing |
title_short |
A study on the impact of artificial intelligence on talent sourcing |
title_full |
A study on the impact of artificial intelligence on talent sourcing |
title_fullStr |
A study on the impact of artificial intelligence on talent sourcing |
title_full_unstemmed |
A study on the impact of artificial intelligence on talent sourcing |
title_sort |
A study on the impact of artificial intelligence on talent sourcing |
publishDate |
2024 |
container_title |
IAES International Journal of Artificial Intelligence |
container_volume |
13 |
container_issue |
1 |
doi_str_mv |
10.11591/ijai.v13.i1.pp1-8 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178164009&doi=10.11591%2fijai.v13.i1.pp1-8&partnerID=40&md5=01d7e561f0846f3fb88f80dedbd04ec6 |
description |
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. |
publisher |
Institute of Advanced Engineering and Science |
issn |
20894872 |
language |
English |
format |
Article |
accesstype |
All Open Access; Gold Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1809678156091621376 |