Artificial Intelligence (AI) is reshaping education by enabling personalised learning experiences, data-driven decision-making, and innovative teaching methodologies. However, despite its potential, widespread AI adoption in educational settings is hindered by significant challenges, particularly in educator preparedness, ethical considerations, and institutional support. This paper synthesises recent research and case studies to examine these barriers and presents a structured approach to equip educators with the necessary skills, competencies, and support to integrate AI effectively and responsibly.

Building on the T.E.A.C.H. A.I. Model, which emphasises hands-on learning, continuous professional development, and ethical AI literacy, this paper introduces the Multi-Dimensional AI Readiness Framework. This framework incorporates three critical dimensions essential for AI adoption in education:
(i) Technical proficiency – equipping educators with AI literacy, tool mastery, and data-driven teaching strategies.
(ii) Pedagogical adaptability – ensuring AI integration aligns with student-centered learning, curriculum design, and innovative instructional methods.
(iii) Ethical governance – fostering responsible AI use by addressing data privacy, algorithmic bias, and transparency in decision-making.

Recognising that AI readiness requires institutional and systemic support, this framework is reinforced by three supporting pillars:
1. Professional development & continuous learning – ensuring educators have access to AI-focused training, mentorship programs, and certification pathways.
2. Institutional support & leadership commitment – promoting AI-driven pedagogical transformation through school leadership engagement and investment in AI-ready infrastructure.
3. Collaborative ecosystems & industry partnerships – fostering interdisciplinary collaboration between educators, AI experts, and EdTech companies to facilitate knowledge exchange and best practices.

This paper highlights the necessity of structured professional development programs, policy-driven incentives, and collaborative learning networks that move beyond conventional training structures. It also emphasises the importance of embedding ethical AI literacy into professional development initiatives to ensure transparency, fairness, and accountability in AI-driven education.

By addressing the gaps between AI innovation and classroom application, this paper presents a scalable roadmap for AI integration that aligns with educators’ evolving needs. The insights provided offer practical guidance for policymakers, academic institutions, and professional development providers, ensuring educators are empowered to leverage AI effectively, ethically, and equitably in modern learning environments.

Keywords: AI in Education, AI Readiness, Educator Professional Development, Ethical AI Integration, Digital Pedagogy, Institutional AI Policies, Future of Learning, AI in Educator Training.