An Assessment of The Talent Management Practices At Aceh Government: A Way Forward In Leveraging AI
This study aims to assess talent management practices within the Aceh Government and look into the potential use of Artificial Intelligence (AI) to improve existing strategies. The utilization of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to summarize relevant research aims to enhance talent acquisition, retention, and development within the government sector. This study will conduct a literature review on methods for managing talent and the integration of AI in government, using the PRISMA approach. This article suggests integrating AI into talent management in the Aceh Government. The text is a thorough review that provides practical advice for effectively tackling challenges in talent management. The article seeks to suggest solutions for optimizing talent processes and enhancing organizational performance by exploring the benefits and limitations of AI integration in the Aceh Government. The assessment will provide guidance for the integration of AI in talent management within the Aceh Government, assisting decision-makers in aligning policies with government objectives. The paper will explore the ramifications of AI in talent management, encompassing advancements in efficiency, augmented decision-making capabilities, and tailored development initiatives. This study will tackle issues such as data protection and workforce preparedness, providing suggestions for optimizing the advantages of AI. This study offers a thorough evaluation of talent management within the Aceh Government and proposes the incorporation of AI to improve its efficacy.
Authors
- Rajermani Thinakaran (ORCID: https://orcid.org/0000-0002-9525-8471)
- Marini Othman (ORCID: https://orcid.org/0000-0002-2358-3013)
- Vidra Rinata
Institutions
- INTI International University (MY)
Publication Details
- Published
- 2024-09-05
- DOI
- https://doi.org/10.1109/ciite62244.2024.10987583
- Primary Topic
- Human Resource and Talent Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00