Identification of HRM Improvement Strategy Using Artificial Intelligence in Modern Economic Development
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Autores: Sabil Sabil
, B.M.A.S. Anaconda Bangkara, Tini Mogea, Ery Niswan, Elkana Timotius
- Localización: International Journal of Professional Business Review: Int. J. Prof.Bus. Rev., ISSN 2525-3654, ISSN-e 2525-3654, Vol. 8, Nº. 6, 2023 (Ejemplar dedicado a: Continuous publication; e01278)
- Idioma: inglés
- Enlaces
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Resumen
Purpose: This literature review study aims to identify HRM improvement strategies using artificial intelligence (AI) in modern economic development.
Theoretical framework: The study will review existing literature and synthesize the findings to identify best practices and key strategies for implementing AI in HRM. The study will focus on the role of AI in HRM improvement and explore how AI can be used to enhance recruitment, training, performance management, and employee engagement.
Design/methodology/approach: Literature review, the search approach will include keywords and Boolean operators to guarantee that relevant research is located. The study questions and goals will define the inclusion and exclusion criteria. The study will also look at the hurdles of implementing AI in HRM and recommend overcoming them.
Findings: The findings of this study will be helpful for organizations seeking to improve their HRM practices using AI and for researchers interested in the intersection of AI and HRM in modern economic development.
Research, Practical & Social implications: The results of the study are useful for policymakers in identifying strategies to improve human resource management using artificial intelligence (AI) in modern economic development.
Originality/value: The research value of this text is its suggestions for conducting more research on how AI affects HRM processes and employee engagement, for creating clear rules and standards for the ethical use of AI in HRM, for teaching HR professionals how to use AI-powered HRM tools and strategies effectively, for fostering collaboration between academic researchers, business leaders, government officials, and other stakeholders, and for overseeing the effects of AI.
