<![CDATA[This study examined the Artificial Intelligence (AI) skills gap among event professionals in Indonesia and developed a contextual training framework to address this issue. A qualitative descriptive approach was employed through in-depth interviews and focus group discussions with event professionals in Bali and Jakarta. The findings indicated that although AI was widely perceived as useful for improving efficiency, significant skill gaps remained at both operational (e.g., prompt engineering, content creation) and strategic levels (e.g., data analytics, AI integration). These gaps were primarily influenced by limited time, high workload, and resistance to technological change. Furthermore, the study identified that existing training programs were often too generic and lacked practical relevance. Therefore, an effective AI training framework should be context-specific, flexible, and application-oriented, incorporating micro-learning formats, case-based learning, and industry practitioner involvement. The study contributed theoretically to AI skills gap literature and practically offered a structured training model to enhance workforce readiness in the event industry.]]>
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