Artificial Intelligence is hugely changing the face of education in India at every level, from preschool upward. The national policies, especially the NEP 2020, have very specifically emphasized incorporating AI and digital technologies into teaching-learning processes and governance. The AI curricula for middle and secondary grades, along with technical syllabi revisions, have been mentioned. Newer platforms and models of governance that promise evidence-based decision-making proliferate. Earlier pilots demonstrated that personalization in learning and inclusion could be offered through AI tools; for instance, adaptive tutoring systems improved student outcomes by replacing ineffective teaching. Language AI is trying to breach the linguistic barriers for schools across India. There are, however, some great challenges, such as India's digital divide- only about 57% of schools have computers, and about 54% have internet connectivity- which can increase inequity in low- and middle-income countries. Concerns regarding data privacy, algorithmic bias, and dehumanization of pedagogy have been well elaborated elsewhere. We synthesize the literature, from 2016 to 2026, across academic studies, government documents, and think tank reports, in this review. The roles of AI in curriculum, governance, teacher development, personalized learning, and data-driven policymaking are reviewed, taking case examples from Punjab and Odisha states and programs like DIKSHA/NISHTHA, which illustrate key roles played by AI within such areas. A brief mention follows of some key challenges equity, ethics, infrastructure, and teacher-student relationships-and policy implications. Overall, evidence suggests that while AI-driven reforms may yield a more student-centered, efficient education, good governance, inclusive design, and massive capacity building will be necessary for its realization.

Key Words :Artificial Intelligence; Education Policy; Governance; Digital Education; Learning Analytics; Ethical AI; Personalized Learning