This systematic review examined the impact of artificial intelligence (AI) technologies on early childhood education, with a focus on their implementation in basic education schools. The study aimed to identify the benefits, barriers, and strategies associated with using AI to personalize learning and foster cognitive development in children, compared to traditional educational methods. Employing the PICOC framework, the review selected relevant studies that demonstrated how AI enhances learning personalization, improves knowledge retention, and supports the development of critical cognitive skills. The findings revealed that AI technologies, particularly neural networks and intelligent tutoring systems, significantly improved adaptive learning experiences by tailoring educational content to individual needs. The use of these technologies achieved a 70% effectiveness rate in personalizing instruction, contributing to increased cognitive engagement and better memory retention. However, the integration of AI in early education faced notable challenges, including insufficient technological infrastructure and inadequate teacher training. This review underscored the potential of AI to revolutionize early childhood education while identifying key obstacles that must be addressed. The study provided evidence-based recommendations for policymakers and educators to facilitate the effective and equitable adoption of AI technologies, emphasizing their role in creating more inclusive and student-centered learning environments. These insights highlight the transformative possibilities of AI in education and serve as a foundation for future research aimed at overcoming implementation barriers.