The integration of Generative Artificial Intelligence (AI) into education presents both opportunities and challenges. This paper explores how Generative AI can enhance learning experiences, personalize education, and foster creativity. However, it also addresses ethical dilemmas, data privacy concerns, algorithmic biases, and the evolving role of educators. The paper emphasizes the importance of ethical guidelines, algorithmic transparency, and inclusive design principles in AI integration. It advocates for educator training and collaboration among stakeholders to ensure responsible AI use. While Generative AI holds promise for transforming education, its integration requires careful consideration of ethical, social, and pedagogical implications. The paper provides strategies for addressing these challenges, including promoting ethical guidelines, ensuring algorithmic transparency, and empowering educators through training and collaboration. It also highlights the need for ongoing dialogue among educators, policymakers, technologists, and students to guide responsible AI integration. The research aims to investigate the integration of Generative AI in education, focusing on its opportunities and challenges. It seeks to explore how Generative AI can enhance teaching and learning, personalize education, and foster creativity while examining ethical, social, and pedagogical implications. The paper provides insights into effective strategies for navigating these challenges, including promoting ethical guidelines, ensuring algorithmic transparency, and empowering educators through training and collaboration. Ultimately, the research aims to contribute to the discourse on responsible AI integration in education and facilitate the creation of more inclusive, engaging, and effective learning environments for all learners. The research is important because it addresses a timely and critical issue at the intersection of technology and learning. Understanding how AI can enhance teaching and learning experiences, personalize education, and foster creativity is essential for educators, policymakers, technologists, and other stakeholders in the education sector. The research also addresses the ethical, social, and pedagogical implications associated with AI integration, highlighting the need for responsible implementation and consideration of diverse perspectives. By providing insights into effective strategies for navigating these challenges, such as promoting ethical guidelines and ensuring algorithmic transparency, the research contributes to the development of best practices for AI integration in education. The research objectives include investigating the current landscape of Generative AI integration in educational practices, examining its potential benefits, identifying ethical, social, and pedagogical implications, exploring strategies for addressing challenges, investigating its impact on teaching practices, student engagement, and learning outcomes, and proposing recommendations for policymakers, educators, and other stakeholders. The research questions focus on the primary benefits and challenges of integrating Generative AI into education and how these impact teaching effectiveness, personalized learning experiences, and student creativity. The literature review discusses the introduction of Generative AI in education, its historical development, current trends, benefits, challenges, and ethical considerations. The conceptual framework outlines three core pillars: opportunities, challenges, and strategies for effective implementation. The methodology includes a mixed-methods approach, with qualitative and quantitative data collection and analysis. The results and discussion highlight the transformative potential of Generative AI in education, its challenges, and the need forThe integration of Generative Artificial Intelligence (AI) into education presents both opportunities and challenges. This paper explores how Generative AI can enhance learning experiences, personalize education, and foster creativity. However, it also addresses ethical dilemmas, data privacy concerns, algorithmic biases, and the evolving role of educators. The paper emphasizes the importance of ethical guidelines, algorithmic transparency, and inclusive design principles in AI integration. It advocates for educator training and collaboration among stakeholders to ensure responsible AI use. While Generative AI holds promise for transforming education, its integration requires careful consideration of ethical, social, and pedagogical implications. The paper provides strategies for addressing these challenges, including promoting ethical guidelines, ensuring algorithmic transparency, and empowering educators through training and collaboration. It also highlights the need for ongoing dialogue among educators, policymakers, technologists, and students to guide responsible AI integration. The research aims to investigate the integration of Generative AI in education, focusing on its opportunities and challenges. It seeks to explore how Generative AI can enhance teaching and learning, personalize education, and foster creativity while examining ethical, social, and pedagogical implications. The paper provides insights into effective strategies for navigating these challenges, including promoting ethical guidelines, ensuring algorithmic transparency, and empowering educators through training and collaboration. Ultimately, the research aims to contribute to the discourse on responsible AI integration in education and facilitate the creation of more inclusive, engaging, and effective learning environments for all learners. The research is important because it addresses a timely and critical issue at the intersection of technology and learning. Understanding how AI can enhance teaching and learning experiences, personalize education, and foster creativity is essential for educators, policymakers, technologists, and other stakeholders in the education sector. The research also addresses the ethical, social, and pedagogical implications associated with AI integration, highlighting the need for responsible implementation and consideration of diverse perspectives. By providing insights into effective strategies for navigating these challenges, such as promoting ethical guidelines and ensuring algorithmic transparency, the research contributes to the development of best practices for AI integration in education. The research objectives include investigating the current landscape of Generative AI integration in educational practices, examining its potential benefits, identifying ethical, social, and pedagogical implications, exploring strategies for addressing challenges, investigating its impact on teaching practices, student engagement, and learning outcomes, and proposing recommendations for policymakers, educators, and other stakeholders. The research questions focus on the primary benefits and challenges of integrating Generative AI into education and how these impact teaching effectiveness, personalized learning experiences, and student creativity. The literature review discusses the introduction of Generative AI in education, its historical development, current trends, benefits, challenges, and ethical considerations. The conceptual framework outlines three core pillars: opportunities, challenges, and strategies for effective implementation. The methodology includes a mixed-methods approach, with qualitative and quantitative data collection and analysis. The results and discussion highlight the transformative potential of Generative AI in education, its challenges, and the need for