TY - JOUR
T1 - Exploring the nexus of artificial intelligence in talent acquisition
T2 - Unravelling cost-benefit dynamics, seizing opportunities, and mitigating risks
AU - Khan, Sania
AU - Faisal, Shaha
AU - Thomas, George
N1 - Publisher Copyright:
© Sania Khan, Shaha Faisal, George Thomas, 2024.
PY - 2024
Y1 - 2024
N2 - The rise in talent management complications led organizations to rely on the latest technologies to automate their routine HRM tasks through AI. This study proposed to examine fundamental aspects of AI in talent acquisition (cost-benefit, opportunities, and risk factors) from the context of strategic analysis and decision-making. 52 respondents from HRM and the information technology departments from fifteen large dairy enterprises, each with more than one thousand employees, were included in the focus group discussion. Both departments were included in the focus group discussion as they heavily employ AI in talent acquisition. The opinions were collected in multiple rounds based on the cost, benefit, opportunity, and risk criteria using the analytical hierarchy process, a multi-criteria decision-making framework. The findings demonstrated that most respondents opinioned AI supports talent acquisition with many opportunities (38.7%) that involve the identification of the best applicants (18.7%) and different benefits (33.2%) to the organization in the form of saving time and cost (16.1%) leading to higher efficacy. The study infers that the application of AI in HRM significantly contributes to talent acquisition, streamlining processes, improving efficiency, and enhancing decision-making. The study recommends that implementing AI in talent acquisition requires a strategic approach, and organizations need to consider factors such as data privacy, ethical use of AI, and ongoing training to ensure successful integration into their hiring processes. Additionally, regular monitoring and adjustments are essential to optimize the effectiveness of AI tools in talent acquisition.
AB - The rise in talent management complications led organizations to rely on the latest technologies to automate their routine HRM tasks through AI. This study proposed to examine fundamental aspects of AI in talent acquisition (cost-benefit, opportunities, and risk factors) from the context of strategic analysis and decision-making. 52 respondents from HRM and the information technology departments from fifteen large dairy enterprises, each with more than one thousand employees, were included in the focus group discussion. Both departments were included in the focus group discussion as they heavily employ AI in talent acquisition. The opinions were collected in multiple rounds based on the cost, benefit, opportunity, and risk criteria using the analytical hierarchy process, a multi-criteria decision-making framework. The findings demonstrated that most respondents opinioned AI supports talent acquisition with many opportunities (38.7%) that involve the identification of the best applicants (18.7%) and different benefits (33.2%) to the organization in the form of saving time and cost (16.1%) leading to higher efficacy. The study infers that the application of AI in HRM significantly contributes to talent acquisition, streamlining processes, improving efficiency, and enhancing decision-making. The study recommends that implementing AI in talent acquisition requires a strategic approach, and organizations need to consider factors such as data privacy, ethical use of AI, and ongoing training to ensure successful integration into their hiring processes. Additionally, regular monitoring and adjustments are essential to optimize the effectiveness of AI tools in talent acquisition.
KW - analytical hierarchy process
KW - artificial intelligence
KW - talent acquisition
KW - talent management
UR - http://www.scopus.com/inward/record.url?scp=85186963171&partnerID=8YFLogxK
U2 - 10.21511/ppm.22(1).2024.37
DO - 10.21511/ppm.22(1).2024.37
M3 - Article
AN - SCOPUS:85186963171
SN - 1727-7051
VL - 22
SP - 462
EP - 476
JO - Problems and Perspectives in Management
JF - Problems and Perspectives in Management
IS - 1
ER -