<![CDATA[This research aims to map teacher readiness profiles in integrating Artificial Intelligence (AI) and evaluate the impact of formal training on these profiles. Using the Gaussian Mixture Model (GMM) as a soft clustering approach to identify natural and flexible groupings of teacher characteristics, data were analyzed from a convenience sample of 67 primary school teachers in Magelang Regency. Three distinct profiles were identified: Low Readiness, Moderate Enthusiast, and High-Adaptive Readiness. The results show that the majority of teachers (80.6%) belong to the High-Adaptive profile, characterized by high literacy and positive attitudes. Furthermore, Chi-Square analysis and Cramer’s V (V=0.1120) revealed no significant relationship between training history and readiness profiles (p=0.6567). This suggests that current formal training has a marginal practical effect. Policy recommendations emphasize the need for differentiated training and structural support to enhance AI integration effectively.]]>
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