Gap Analysis in Strategic Upskilling: The Impact of Artificial Intelligence on Hris Practices and Workforce Development
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Gap Analysis in Strategic Upskilling: The Impact of Artificial Intelligence on Hris Practices and Workforce Development Abstract This study, titled "Gap Analysis in Strategic Upskilling: The Impact of Artificial Intelligence on HRIS Practices and Workforce Development," investigates the role of Artificial Intelligence (AI) in enhancing Human Resource Information Systems (HRIS) to address workforce development challenges. Using a mixed-methods approach, including bibliometric analysis and systematic review, the research identifies gaps in current HRIS practices and explores AI-driven solutions for strategic upskilling. The findings reveal that AI enhances HR efficiency by automating tasks, enabling data-driven decisions, and providing personalized upskilling pathways. However, challenges such as data fragmentation, ethical concerns, and employee resistance hinder adoption. This study highlights the importance of developing ethical frameworks, fostering employee trust, and leveraging AI to align workforce skills with organizational goals. By offering actionable insights for organizations, policymakers, and educators, this research emphasizes AI’s transformative potential while advocating for further interdisciplinary and longitudinal studies to ensure sustainable workforce growth in the digital era. Keywords: Artificial Intelligence, Human Resource Management, Gap Analysis, PRISMA Framework, Systematic Review, SWOT Analysis, Upskilling Suggested Citation: Budi Susilo, Yudi Kurniawan and Noordin, Nurulhuda and Abdul Razak, Fariza Hanis, Gap Analysis in Strategic Upskilling: The Impact of Artificial Intelligence on Hris Practices and Workforce Development. Available at SSRN: https://ssrn.com/abstract=5118512 or http://dx.doi.org/10.2139/ssrn.5118512
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The research methodology for this study, titled "Gap Analysis in Strategic Upskilling: The Impact of Artificial Intelligence on HRIS Practices and Workforce Development," was designed to systematically analyze and address research questions related to the integration of Artificial Intelligence (AI) in Human Resource Information Systems (HRIS). It identifies gaps in HRIS practices, highlights opportunities for strategic upskilling, and evaluates workforce development strategies. A mixed-methods approach is employed, combining bibliometric analysis, systematic review, and analytical frameworks to produce comprehensive and actionable insights. 3.1 Research Design This study adopts a mixed-methods approach, combining qualitative and quantitative research techniques to thoroughly investigate the intersection of artificial intelligence (AI) and Human Resource Information Systems (HRIS) in the context of strategic workforce upskilling. To achieve a comprehensive understanding, several tools and platforms were employed throughout the research process. The Scopus Database served as the primary source for peer-reviewed literature. This platform provided access to an extensive collection of articles related to HRIS, AI integration, and workforce upskilling. Leveraging Scopus ensured that the research was built upon a foundation of high-quality, reliable, and relevant academic studies. To identify research trends and visualize relationships among keywords, authors, and affiliations, VOSviewer was employed for bibliometric mapping. This tool proved invaluable in highlighting areas of extensive research as well as gaps that warrant further exploration. By creating visual representations of connections within the literature, VOSviewer offered insights into underexplored domains within the field. Citations metrics were analyzed using Harzing’s Publish or Perish to identify impactful and highly influential works in the domain. This step was crucial in ensuring the inclusion of foundational and groundbreaking studies that shaped the field. Lastly, Microsoft Excel was utilized for data organization and analysis. Bibliometric data was systematically structured, and visualizations of research trends were created to facilitate a clearer interpretation of findings. Excel also played a key role in summarizing and presenting data in a cohesive format. By integrating these tools, the study established a robust methodology for identifying research gaps, analyzing emerging trends, and framing actionable recommendations. This multifaceted approach ensured that the research was both thorough and methodologically sound.
Institutions
- Universiti Teknologi MARA
- Cyberjaya University College of Medical Sciences