AI-Driven HR Optimization Strategies in Finance and Marketing: Methodological Framework and Applications

Lekshmi, R.S. and Mary, V. Sheela and Arasuraja, G. and Krishnamoorthy, V. and Kaliappan, S. and Selvameena, R. (2024) AI-Driven HR Optimization Strategies in Finance and Marketing: Methodological Framework and Applications. In: UNSPECIFIED.

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Abstract

The proposed systems that include AI and the IoT present innovative financial and marketing opportunities. AI analytics capabilities and networked devices with the capability to provide real-time data mean the possibility to significantly improve recruitment, employee engagement, performance management, and retention. It combines natural language processing and machine learning algorithms, offering personalized recommendations, and in the vision insights, and in the case of environmental sensors, smart devices, and wearable health monitors, it facilitates accumulation of significant data. This framework will integrate IoT with AI to enhance HR procedures: more engaging, efficient, and enjoyable work environment. Apart from better decision-making and automated occupations, it also advocates for a data-driven approach to HRM. Further, it can result in the formation of intelligent and responsive HR systems that have the potential of improving organizational effectiveness and work productivity. © 2025 Elsevier B.V., All rights reserved.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computer Science > Artificial Intelligence
Computer Science > Computer Science Applications
Computer Science > Information Systems and Management
Computer Science > Computer Networks and Communications
Computer Science > Computer Vision and Pattern Recognition
Engineering > Electrical and Electronic Engineering
Physics and Astronomy > Instrumentation
Divisions: Arts and Science > Vinayaka Mission's Kirupananda Variyar Arts and Science College, Salem, India > Computer Application
Depositing User: Unnamed user with email techsupport@mosys.org
Last Modified: 27 Nov 2025 07:10
URI: https://ir.vmrfdu.edu.in/id/eprint/2102

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