Ramya, S.S and Saikrishnan, S and Sumathi, S and Kamalakannan, S and Sri Keerthana, J and Indhumathi, G (2024) Optimizing the Strategic Fusion of IoT and AI for Enhanced HR Performance in Stocks. Optimizing the Strategic Fusion of IoT and AI for Enhanced HR Performance in Stocks. pp. 697-702.

[thumbnail of Optimizing the Strategic Fusion of IoT and AI for Enhanced HR Performance in Stocks.PDF] Text
Optimizing the Strategic Fusion of IoT and AI for Enhanced HR Performance in Stocks.PDF - Published Version
Download (1MB)

Abstract

Organizations are constantly exploring new
technological avenues to enhance their human resources
operations. This study explores the potential advantages of
incorporating the technologies of artificial intelligence with the
Internet of things into HR operations. This paper aims to
provide a thorough examination of prior research and case
studies, shedding light on the benefits, drawbacks, and optimal
approaches related to this merger. Companies are closely
examining both their internal human resources (HR)
processes and their external recruiting efforts. Utilizing
empirical data and qualitative research, this paper adopts a
mixed-methods approach to offer practical implementation
recommendations. There are several benefits to consider, such
as cost savings, improved recruitment, increased employee
motivation, and more efficient performance evaluation.
Addressing concerns such as data security, complex
integration, and a lack of expertise is crucial. When it comes to
HR productivity and efficiency, organizations can greatly
benefit from the combination of IoT and AI. By adopting a
strategic approach that emphasizes collaboration and careful
planning, businesses can maximize their gains

Item Type: Article
Uncontrolled Keywords: Institutions, Technology Integration, Optimization, Recruitment, Internal Operations, Data Security, Collaboration
Divisions: PSG College of Arts and Science > Department of Commerce
PSG College of Arts and Science > Department of Corporate Secretaryship
Depositing User: Dr. B Sivakumar
Date Deposited: 11 Dec 2025 05:46
Last Modified: 11 Dec 2025 05:46
URI: https://ir.psgcas.ac.in/id/eprint/2579

Actions (login required)

View Item
View Item