With advancements in AI technology, its application in recruitment has gained prominence due to potential benefits such as increased efficiency, improved candidate selection, and reduced bias. This thesis aims to explore the factors that influence the utilization of Artificial Intelligence (AI) in the recruitment process and provides insights on how organizations can leverage these factors to optimize recruitment outcomes. However, several factors impact the successful utilization of AI in recruitment processes. By examining these factors through a comprehensive literature review and empirical analysis, this research emphasize to identify the challenges and opportunities associated with AI implementation in recruitment. Moreover, this study seeks to provide insights for organizations to effectively leverage these factors to optimize recruitment outcomes. The findings highlights the impact of AI adoption in recruitment and identifies strategies and practices that organizations can employ to optimize recruitment outcomes through AI utilization. This study emphasised to combine these strategies to build trust and ensuring transparency and explainability of AI algorithms, and addressing potential biases and discrimination. By examining the factors that influence AI adoption in recruitment, this research provides valuable insights for HR professionals and organizational leaders to leverage AI effectively in the recruitment process. This thesis emphasizes the importance AI adoption in recruitment and taking measures to maximize benefits and minimize risks. It contributes to the expanding knowledge on AI in recruitment, enabling organizations to make informed decisions and optimize recruitment outcomes in the digital transformation era.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-510527 |
Date | January 2023 |
Creators | Chowdhury, Moumita Hom |
Publisher | Uppsala universitet, Företagsekonomiska institutionen |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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