Generative artificial intelligence is increasingly transforming education by enabling adaptive learning environments, personalized instructional support, and collaborative knowledge creation, while also assisting research, assessment, and academic administration. In the context of fifth generation education systems, the integration of generative artificial intelligence offers new opportunities to enhance student engagement, support innovative pedagogical practices, and improve scholarly productivity. This study presents a systematic review of recent research on the adoption of generative artificial intelligence in primary, secondary, and higher education institutions, using established guidelines for systematic literature reviews and bibliometric analysis. The review examines applications of generative artificial intelligence for learners, educators, and researchers, and identifies key challenges including academic integrity risks, algorithmic bias, ethical concerns, data privacy issues, and unequal access to advanced educational technologies. By analyzing research trends, thematic relationships, and existing gaps, this study provides insights for the design of adaptive learning systems, the promotion of responsible use of artificial intelligence in education, and the direction of future research efforts. Overall, the findings highlight the potential of generative artificial intelligence to support human machine collaboration, lifelong learning, and inclusive educational environments, offering practical guidance for policymakers, educators, and engineers seeking to apply artificial intelligence for meaningful educational impact.

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