Aim/Purpose: Evaluate teachers’ perceptions, strategies, and challenges in integrating artificial intelligence (AI) into K-12 education and identify patterns and trends in the data from the reviewed studies. Background: This systematic review examines a decade of innovation to explore the transformative impact of AI on education (2014–2024). Adhering to PRISMA 2020 guidelines, the study uncovers key trends, challenges, and breakthroughs in AI-driven teaching and learning, offering a comprehensive perspective on how AI reshapes educational practices and methodologies. Methodology: The study employs a systematic review to analyze the implementation of AI techniques and tools in primary education, following the PRISMA 2020 guidelines to ensure the reliability and effectiveness of the findings. To achieve this, an extensive search was conducted in academic databases such as Web of Science, Scopus, and ERIC, focusing on empirical studies and peer-reviewed articles published between 2014 and 2024. Only accessible, peer-reviewed articles classified under Education and Educational Research and published in English or Spanish were selected. The search strategy was structured into five categories aligned with the research questions to identify relevant studies accurately. The selection process was carried out in three phases – Identification, Screening, and Inclusion – applying predefined criteria to guarantee the quality and relevance of the selected studies. Of an initial total of 514,919 articles, 488,940 were excluded for not meeting the inclusion criteria. After removing duplicates and evaluating titles, abstracts, and full texts, a final set of 28 studies was included. Contribution: The study explores the integration of AI in primary education, revealing both teachers’ enthusiasm and the challenges they face. While AI is perceived as a tool to enhance critical thinking, problem-solving, and student engagement, its implementation is limited by insufficient training, resources, and institutional support. Despite these obstacles, teachers show confidence in designing AI-integrated curricula, though this is weakened by inadequate infrastructure and technical support, highlighting the need for continuous professional development. The study also stresses the importance of establishing a competency framework for AI literacy and adopting a systemic approach to AI education. Additionally, ensuring safe learning environments by addressing data privacy and AI biases remains a key challenge. Overcoming these issues is essential for the ethical and effective integration of AI, maximizing its benefits while safeguarding student equity and security. Findings: - Educators see the potential of AI to personalize learning. - Barriers are lack of training and resources for teachers. - Importance of continuous training in digital skills. - Need for policies that promote AI literacy. - Collaboration with experts to optimize AI in the classroom. Recommendations for Practitioners: Teachers are encouraged to collaborate in using AI tools to enhance educational outcomes, supported by continuous professional development programs, clear policies that safeguard privacy and promote equality, and a framework that preserves human autonomy in integrating AI technologies. Recommendation for Researchers: The lack of empirical research on AI interventions in education limits understanding of its true impact, highlighting the need for future studies to fill this gap and optimize its application for greater educational benefits. Impact on Society: The integration of AI in K-12 education is not just an opportunity; it is a necessity to prepare future generations for an increasingly digital world. While AI has the potential to revolutionize learning by fostering critical thinking, personalization, and engagement, its impact depends on how effectively it is implemented. To ensure its benefits, it is essential to empower educators and students with AI literacy, address issues like bias and data privacy, and establish robust legal frameworks for fair and transparent use. Without proactive policies, AI could widen educational inequalities instead of reducing them. A responsible, human-centered approach is needed to create an inclusive, ethical, and effective AI-powered education system. Future Research: The article highlights the urgency of future empirical research to better understand the real impact of AI in education, as the lack of intervention studies limits its optimal application. Analyzing how AI influences learning outcomes, teaching dynamics, equity, and accessibility is essential, along with investigating the pedagogical competencies and technological conditions that affect its adoption. To this end, expanding the scope of studies is recommended by incorporating multicultural and multilingual perspectives, exploring AI applications across various disciplines and educational levels, and promoting interdisciplinary approaches that address ethical, social, and pedagogical dimensions.