The emergence of agentic AI is transforming education by enabling highly personalized learning pathways that
cater to the unique needs, interests, and abilities of every learner. This paper explores the role of agentic AI systems—
autonomous, proactive agents capable of setting goals, orchestrating complex workflows, and adapting in real time—in
transforming traditional one-size-fits-all educational paradigms. We analyze the mechanisms through which agentic AI
dynamically assesses learner profiles, recommends individualized content, and modifies instructional strategies in response to
student progress and feedback. The research highlights the AI‘s capabilities in fostering learner agency, supporting diverse
learning styles, and addressing equity and inclusion in digital education environments. Empirical case studies and simulated
deployments demonstrate increased student engagement, improved mastery, and the potential for reduced learning gaps.
Challenges surrounding interpretability, data privacy, and ethical AI design are critically examined, offering guidelines for
safe, scalable, and impactful implementation. Through this interdisciplinary inquiry, the paper establishes agentic AI as a
cornerstone technology for the next generation of adaptive, learner-centered educational systems.
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