<p>The rapid evolution of Artificial Intelligence (AI) has prompted the need for AI education in K-12 settings to foster AI literacy among students. However, research has primarily focused on student perspectives on learning about AI, and little attention has been paid to teacher perspectives on AI education in K-12 contexts. To address this gap, this study examined the factors influencing teacher intention to teach AI. A conceptual research model was designed based on the integration of the self-determination theory and the motivation–opportunity–ability framework. Data were collected from 230 South Korean teachers who have different levels of experience in AI education. The findings revealed that teachers’ intentions were generally comparable across the demographic factors of gender and age but differed significantly based on prior experience in AI education. Additionally, autonomous motivation was the strongest predictor of teaching intention and was significantly influenced by teachers’ satisfaction with autonomy, competence, and relatedness. Controlled motivation also had a significant but lower effect, whereas amotivation negatively impacted intentions. Further analysis revealed that self-efficacy moderated the relationship between autonomous motivation and AI teaching intention. Students’ readiness also moderated the relationship between controlled motivation and intention, and the negative influence of amotivation was moderated by both self-efficacy and supportive resources. Based on these findings, theoretical and practical implications to better support AI education are provided.</p>