This paper presents a bibliometric analysis of the impact of artificial intelligence (AI) on teaching practices, using data from Scopus and Web of Science databases over the period 2018–2023. The study aims to provide insights into the scientific production, collaboration patterns, key research areas, and emerging trends in the field of AI in education. Key findings include: 1. **Scientific Production**: The annual growth rate of scientific publications on AI in teaching is significant, with Scopus showing a 25.42% annual growth and Web of Science a 39.33% annual growth. China, USA, India, Germany, UK, and Spain are the most active countries in this field. 2. **Impact of Publications**: China leads in citations, followed by the USA and UK. The most cited articles discuss the opportunities and challenges of AI in education, particularly focusing on ChatGPT and large language models. 3. **Collaboration Patterns**: International collaboration is evident, with clusters of researchers from different countries and institutions working together. Some teams work in isolation, but overall, the field shows strong global connectivity. 4. **Key Research Areas and Trends**: The main research areas include techniques such as AI, machine learning, and deep learning, as well as technologies like ChatGPT, learning analytics, and virtual reality. Emerging trends highlight the increasing role of AI and machine learning in teaching practices. 5. **Discussion and Conclusions**: The study emphasizes the transformative potential of AI in education, highlighting both benefits and potential risks. It calls for ongoing attention, collaboration, and ethical considerations to integrate AI effectively into educational practices. The research underscores the need for further exploration of AI in teaching, particularly in areas such as emotional intelligence, student creativity, and ethical implications, to shape a future where technology enhances learning outcomes and empowers educators.This paper presents a bibliometric analysis of the impact of artificial intelligence (AI) on teaching practices, using data from Scopus and Web of Science databases over the period 2018–2023. The study aims to provide insights into the scientific production, collaboration patterns, key research areas, and emerging trends in the field of AI in education. Key findings include: 1. **Scientific Production**: The annual growth rate of scientific publications on AI in teaching is significant, with Scopus showing a 25.42% annual growth and Web of Science a 39.33% annual growth. China, USA, India, Germany, UK, and Spain are the most active countries in this field. 2. **Impact of Publications**: China leads in citations, followed by the USA and UK. The most cited articles discuss the opportunities and challenges of AI in education, particularly focusing on ChatGPT and large language models. 3. **Collaboration Patterns**: International collaboration is evident, with clusters of researchers from different countries and institutions working together. Some teams work in isolation, but overall, the field shows strong global connectivity. 4. **Key Research Areas and Trends**: The main research areas include techniques such as AI, machine learning, and deep learning, as well as technologies like ChatGPT, learning analytics, and virtual reality. Emerging trends highlight the increasing role of AI and machine learning in teaching practices. 5. **Discussion and Conclusions**: The study emphasizes the transformative potential of AI in education, highlighting both benefits and potential risks. It calls for ongoing attention, collaboration, and ethical considerations to integrate AI effectively into educational practices. The research underscores the need for further exploration of AI in teaching, particularly in areas such as emotional intelligence, student creativity, and ethical implications, to shape a future where technology enhances learning outcomes and empowers educators.