<![CDATA[The development of Artificial Intelligence (AI) technology in the era of the Industrial Revolution 4.0 has encouraged the transformation of learning practices, particularly in vocational education. This study aimed to analyze the readiness of Motorcycle Engineering and Business teachers to integrate AI into the learning process. A descriptive qualitative approach was employed, with data collected through interviews, observations, and documentation. The research subjects consisted of Motorcycle Engineering and Business teachers at SMKN 1 Gerokgak and SMKN 3 Singaraja. Data were analyzed through data reduction, data display, and conclusion drawing. The findings revealed that teachers’ understanding of AI tended to be at the multistructural level of the SOLO Taxonomy, while some teachers had begun to demonstrate relational characteristics. Teachers’ skills in utilizing AI were generally at the manipulation level of Dave’s Psychomotor Taxonomy, with several teachers reaching the precision level. Teachers’ attitudes and perceptions toward AI integration showed a positive tendency and were categorized at the valuing stage of Krathwohl’s Affective Taxonomy. Supporting factors for AI integration included institutional support, training opportunities, adequate facilities and infrastructure, and teachers’ adaptability. Meanwhile, inhibiting factors included disparities in digital competence, limited training access, paid AI features, prompt formulation skills, and challenges in monitoring students’ use of AI. These findings indicate that teachers’ readiness to integrate AI into learning is relatively good; however, further competency development and institutional support are needed to optimize AI implementation in vocational education.]]>
