The Journal for Information Professionals
Asia Pacific Journal of Information Systems (APJIS), a Scopus and ABDC indexed journal, is a
flagship journal of the information systems (IS) field in the Asia Pacific region.
ISSN 2288-5404 (Print) / ISSN 2288-6818 (Online)
Editor : Seung Hyun Kim
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Current Issue
| Date | June 2025 |
|---|---|
| Vol. No. | Vol. 35 No. 2 |
| DOI | https://doi.org/10.14329/apjis.2025.35.2.432 |
| Page | 432~458 |
| Title | Textual Analysis of Effectiveness on Digital Transformation based on Artificial Intelligence Reskilling: Small and Medium Enterprises (SMEs) Cases |
| Author | Hyangmi Kim, Hyo Jin Song, Joon Young Kim |
| Keyword | Digital transformation, Artificial Intelligence, SMEs, Reskilling, PoC Project |
| Abstract | Digital Transformation (DX) is the primary innovation strategy to enhance organizational flexibility and productivity in the workplace. Each company promotes DX within its unique organizational direction and situations, and employee competency becomes a critical factor for successful transformation. However, existing small and medium-sized enterprises (SMEs) have limited resources to hire AI experts or develop appropriate DX implementation strategies compared to large enterprises. As a result, many SMEs adopt a more practical and efficient approach by implementing internal AI reskilling programs for their employees. In this paper, we aim to examine whether such reskilling programs effectively drive DX adaptation within SMEs. For our investigation, we designed AI-based reskilling programs that were implemented across 39 SMEs from diverse industries, alongside Proof of Concept (PoC) projects that were aligned with each company’s DX goals. We extracted key terms from the reskilling program reports and categorized the companies by industry type and organizational scale. We also conducted text analysis to identify strategic directions and transformation intents regarding DX. Our findings demonstrated that AI reskilling programs could effectively support SMEs in achieving DX. Our analysis results also highlight how industry-specific characteristics, and the availability of internal resources influence DX implementation. In particular, the number of employees and the ratio of R&D investment emerged as key factors. Furthermore, this study provides a practical roadmap for AI adoption and strategy tailored to similar types of SMEs, serving as a foundational reference for inclusive and sustainable digital transformation. |
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