Upskilling and Reskilling Strategies as a Response to the Optimization of Artificial Intelligence Utilization in Enhancing Human Resource Quality: A Qualitative Study on XYZ Startup Company - Kadek Devy Ariningsih Chandradilova; Ni Made Ary Widiastini (Ilomata International Journal of Social Science, 2026)
This study aims to examine the upskilling and reskilling strategies implemented by Startup XYZ in response to the integration of artificial intelligence (AI) into its operations. A qualitative single-case study design was employed at a technology-based transportation startup in Bali, Indonesia, during the period of February to April 2025. Five informants were purposively selected, consisting of one HR manager, one line manager, and three employees who had participated in training programs. Inclusion criteria required direct involvement in program planning or participation for at least three months. Data were collected through in-depth interviews (45–60 minutes each), observation of two training sessions (±2 hours each), and document reviews, then analyzed using thematic analysis. The findings show that upskilling enhanced technical competencies, particularly in AI-based data analysis and decision-making, while reskilling facilitated transitions from administrative to AI-related roles. Key supporting factors included strong management commitment, collaboration with training partners, digital infrastructure, and employee readiness. However, challenges were identified, including budget constraints, employee resistance, uneven competencies, and conflicts between training schedules and operational workloads. The study concludes that upskilling and reskilling are effective strategies for improving workforce adaptability and competitiveness in small startups. Practically, modular training design, flexible scheduling, and career development pathways are recommended to overcome financial and psychological barriers, providing a scalable model for other startups undergoing AI-driven transformation.