Abstract: Artificial intelligence (AI) is increasingly recognized as a transformative force for enhancing the quality, equity, and accessibility of education and for accelerating progress toward Sustainable Development Goal 4 (SDG 4), quality education. This study adopts a conceptual analysis approach, integrating a focused exploration of scholarly and policy literature with a strategic SWOT–TOWS analysis of AI applications in education to inform ethical and policy-oriented implementation frameworks. It is anchored in an established taxonomy of AI in education (AIED) systems and a critical socio-technical perspective that treats AI’s educational effects as conditional on governance and institutional context. Rather than a systematic review, it synthesized conceptually relevant publications indexed in Scopus and Web of Science and policy reports from UNESCO and the United Nations. Findings indicate that AI can advance SDG 4 through personalized and adaptive learning, predictive analytics, improved learning outcomes, data-driven decision-making, administrative automation, and expanded access, particularly in resource-constrained contexts. Persistent challenges include algorithmic bias, data privacy risks, inequitable digital access, and diminished human interaction. The SWOT–TOWS synthesis translated these findings into strategic pathways for responsible AI integration. Recommendations include national AI policies that promote inclusive public–private partnerships, culturally representative datasets to mitigate bias, human-in-the-loop safeguards, algorithmic impact assessments, AI literacy initiatives, international collaboration on teacher training, and ethical guidelines that address privacy, fairness, and transparency. Collectively, these strategies underscore that AI’s contribution to SDG 4 is conditional rather than automatic and aim to ensure that AI enables inclusive and equitable quality education and lifelong learning for all.