Artificial Intelligence Readiness and Teacher Instructional Leadership among Public Elementary School Teachers in Tacurong City Division

This study examined the relationship between artificial intelligence (AI) readiness and teacher instructional leadership among public elementary school teachers in Tacurong City Division, Philippines. An explanatory sequential mixed-methods design involved 300 teachers selected through proportionate stratified random sampling and 30 teachers interviewed for qualitative explanations. Data were collected using a validated, researcher-adapted and researcher-developed questionnaire and individual interviews, then analyzed through descriptive statistics, Pearson correlation, multiple linear regression, and thematic analysis. Teachers reported very high AI readiness (M = 4.465, SD = 0.444) and instructional leadership (M = 4.524, SD = 0.450). AI readiness was strongly associated with instructional leadership (r = .806, p < .001), with the regression model explaining 71.7% of its variance (R² = .717). AI Foundations and Applications, AI Pedagogy, and Human-Centered Mindset emerged as significant positive predictors, whereas Ethics of AI and AI for Professional Learning were not significant unique predictors. Qualitative findings highlighted experiential learning, collaboration, instructional preparation, professional judgment, and challenges involving accuracy, accessibility, privacy, and overdependence. The findings indicate significant statistical associations rather than causation. Schools should prioritize practical AI training, collaborative professional development, equitable technological access, and ethical safeguards. Self-reported measures, the single-division setting, and nonexperimental design limit generalizability and causal interpretation. The study provides evidence for sustainable teacher development and responsible AI integration, supporting SDG 4 (Quality Education), with relevance to SDG 9 (Industry, Innovation and Infrastructure) and SDG 10 (Reduced Inequalities).