Content area

Abstract

Artificial Intelligence (AI) has revolutionised knowledge work through generative AI like ChatGPT, impacting coordination, creativity, and problem-solving. As AI adoption accelerates, understanding its implications for Human Resource Development (HRD) becomes crucial. This paper introduces a conceptual framework for HRD strategies in AI transformation, addressing the dearth of research in this area. Utilising a case study approach, we distinguish five strategies: Acceleration, Culture-driven Transformation, Data-Driven Agility, Personalized Learning, and Immersive, emotional Learning at the workplace. Each strategy caters to distinct organisational needs. Challenges include balancing rapid upskilling, managing cultural shifts, ensuring data quality, promoting self-directed learning, and implementing immersive technologies. The framework offers insights for organisations navigating AI-induced transformations in HRD practices. Further research and refinement are essential as AI technology evolves.

Details

1009240
Title
Navigating AI Transformation: Human Resource Development Strategies for Corporate Learning
Author
Volume
17
Issue
4
Pages
80-93
Publication year
2024
Publication date
2024
Section
Papers
Publisher
International Association of Online Engineering (IAOE)
Place of publication
Vienna
Country of publication
Austria
Publication subject
e-ISSN
18675565
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Milestone dates
2024-11-05 (Published); 2023-12-18 (Submitted); 2024-11-05 (Issued); 2024-11-05 (Created); 2024-11-05 (Modified)
ProQuest document ID
3132553050
Document URL
https://www.proquest.com/scholarly-journals/navigating-ai-transformation-human-resource/docview/3132553050/se-2?accountid=208611
Copyright
© 2024. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-07-15
Database
ProQuest One Academic