The impact of automation and artificial intelligence on HR functions in logistics: Challenges and opportunities

Kasilingam, Niraimathi and Devadoss, Anitha Kumari (2024) The impact of automation and artificial intelligence on HR functions in logistics: Challenges and opportunities. In: THE 5TH INTERNATIONAL CONFERENCE ON BUILDINGS, CONSTRUCTION, AND ENVIRONMENTAL ENGINEERING: BCEE5, 21–23 November 2023, Amman, Jordan.

Full text not available from this repository. (Request a copy)

Abstract

Automation and artificial intelligence (AI) have become transformative drivers in the quickly changing logistics business, profoundly altering operating paradigms. The HR (human resources) departments inside logistics organizations are significantly impacted by this tectonic upheaval, which presents both opportunities and challenges. The present study used a descriptive research design, and secondary data collection with a systematic literature review in order to explore automation and AI in HR functions. The present study aims to find the impact of the automation of AI on HR functions, To asses the adaptability of AI on performance management, decision-making, talent management, knowledge management, training, and development and competency mapping. Complex workforce transitions, worries about job displacement, data security issues, and moral quandaries involving AI applications in HR present problems. Despite these obstacles, there are vast opportunities that can be taken advantage of. Automation and AI improve HR productivity by allowing staff to concentrate on strategic projects and data-driven choices and fostering a healthy workplace culture. By streamlining hiring procedures, these solutions guarantee a more competent staff and enable smart workforce planning. The complex interactions between automation, AI, and human resources in logistics are explored in this article.

Item Type: Conference or Workshop Item (Paper)
Subjects: Management Studies > Human Resources
Domains: Management Studies
Depositing User: Mr IR Admin
Date Deposited: 29 Aug 2025 06:04
Last Modified: 29 Aug 2025 06:04
URI: https://ir.vistas.ac.in/id/eprint/10856

Actions (login required)

View Item
View Item