Mechanisms of Change Management for Driving the Integration of Artificial Intelligence (AI) in Private Vocational Education Institutions: A Qualitative Study from the Perspective of Administrators

Abstract

This Qualitative Document Analysis (QDA) primarily aimed to analyze change management mechanisms for integrating Artificial Intelligence (AI) in private vocational education institutions. The study had three main objectives: 1) To analyze strategic mechanisms based on established change management steps; 2) To identify context-specific success factors and challenges; and 3) To synthesize actionable recommendations for AI innovation management. The research proceeded in three phases, utilizing Kotter's 8-Step Model for deductive analysis to extract evidence emphasizing market urgency and establishing an AI-Embedded Vision. Findings revealed the successful mechanism is the “Cost-Benefit Driven Hybrid Change Mechanism.” This model modifies Kotter's steps by using Entrepreneurial Leadership to consolidate implementation phases for rapid deployment. The key success factor identified was Cost-Effectiveness Management, focusing on achieving Return on Investment (ROI) in the short term. Conversely, critical challenges include staff anxiety about being replaced in practical skills streams and the high fluctuation of AI-skilled personnel due to competition from industry. Actionable recommendations synthesized from the study include establishing an “Innovation ROI Evaluation Unit” and continuously investing in “AI Micro-Credentialing Programs” for existing personnel to build sustainability and mitigate resistance. The results confirm and expand the understanding of change management theory within resource-constrained, market-driven organizations.