Bridging the Artificial Intelligence (AI) Gap: Practical Application of AI to Optimize Teaching and Elevate Educational Decision-Making

This study investigated whether structured, job-embedded, asynchronous professional development moved K-12 educators at School Lane Charter School (SLCS), an International Baccalaureate World School, from general AI awareness toward strategic pedagogical integration. A sequential explanatory mixed-methods design combined independent pre-intervention (n = 32) and post-intervention (n = 52) administrations of the Teacher AI Competence Self-Efficacy (TAICS) scale (Chiu et al., 2024) with five interviews and two focus groups, guided by the Technology Acceptance Model (Davis et al., 1989). Three research questions examined the relationship between AI awareness and integration willingness, perceived ease of use and usefulness relative to workload and decision-making efficacy, and perceived contributions to student engagement and instructional practice. No statistically significant differences emerged across the six TAICS subscales between groups, but AI Knowledge self-efficacy correlated significantly with integration willingness (r = +0.37, p = .039), supporting the Technology Acceptance Model’s central relationship. The AI Assessment subscale produced the lowest means at both time points. Qualitative findings identified five themes, including AI as a production efficiency tool, differentiation as the primary application, and prompt literacy as a persistent barrier. The study concludes that AI integration at SLCS remains early-stage and production-oriented, and offers recommendations for prompt literacy instruction, role-differentiated professional development, and institutional AI governance structures.