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Agentic Artificial Intelligence (AI) systems represent a paradigm shift from assistive automation to autonomous decision-making entities capable of independent reasoning, planning, and execution of tasks. While such systems offer efficiency, scalability, and personalization in education and employment domains, their autonomous nature introduces complex legal and regulatory challenges. This paper critically examines the legal implications of deploying agentic AI systems in academic assessment, student evaluation, recruitment, performance appraisal, and workforce decision-making. Through a systematic literature review and doctrinal legal analysis, the study identifies regulatory gaps related to accountability, transparency, algorithmic bias, data protection, and the absence of meaningful human oversight. The findings indicate that existing AI governance frameworks primarily regulate assistive or predictive AI systems and are insufficient to address the risks posed by autonomous agentic systems. The paper proposes a human-centric regulatory framework emphasizing shared liability, explainability, procedural fairness, and enforceable rights for students and workers. This study contributes to the emerging discourse on responsible governance of agentic AI by offering domain-specific legal insights for education and employment decision-making.