Bridging the AI Skills Gap: A Training and Assessment Framework for Event Professionals in Indonesia
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Abstract
Purpose: This study examined the Artificial Intelligence (AI) skills gap among event professionals in Indonesia and aimed to develop a contextual training framework to address this issue.
Method: A qualitative descriptive approach was employed through in-depth interviews and focus group discussions with event professionals in Bali and Jakarta.
Result: The findings indicated that although AI was widely perceived as useful for improving efficiency, significant skill gaps remained at both operational levels (e.g., prompt engineering and content creation) and strategic levels (e.g., data analytics and AI integration). These gaps were primarily influenced by limited time, high workload, and resistance to technological change. Furthermore, existing training programs were often too generic and lacked practical relevance.
Contribution: This study contributes theoretically to the AI skills gap literature and practically offers a structured, context-specific training framework that is flexible and application-oriented, incorporating micro-learning formats, case-based learning, and industry practitioner involvement to enhance workforce readiness in the event industry.
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