The rapid advancement of artificial intelligence (AI) presents transformative opportunities for education by enabling highly personalized learning experiences. This paper introduces the Personalized AI Educational Tutor (PAIET), a framework designed to tailor educational content and strategies to individual students. By integrating machine learning, natural language processing, and adaptive learning algorithms, PAIET creates a dynamic, student-centered learning environment.

The framework leverages user profiling to assess a learner's strengths, weaknesses, preferences, and progress through continuous interaction. A modular design ensures adaptability across various educational contexts, including K-12, higher education, and professional training. PAIET's key components include:
(1) a competency-based curriculum mapping engine,
(2) real-time performance analytics, and
(3) an AI-powered recommendation system for customized content delivery.

This research also addresses ethical considerations, such as data privacy, algorithmic transparency, and equitable access, ensuring that AI adoption enhances educational equity. The results from pilot studies conducted in diverse learning environments demonstrate improved student engagement, retention, and academic outcomes, highlighting the potential of PAIET to revolutionize personalized education.

This paper contributes to the ongoing discourse on the role of AI in education and provides a blueprint for integrating intelligent tutoring systems into modern pedagogical frameworks.

Keywords: AI, Customized Education.