This study investigates the impact of generative artificial intelligence in education, highlighting the importance of educators adapting to the use of new applications, such as ChatGPT, along with the need to explore collaboration between humans and machines to improve teaching and learning outcomes. A systematic review of the world literature was conducted using systematic literature methods and scope and content review, using the Web of Science core database. Specific search terms were applied, and relevant data from the selected documents were exported. Data analysis was performed using VOSviewer software to explore co-authorship, citation, and relevant themes. Qualitative content analysis strategies were used to identify highlights of the summaries and keywords of the documents, based on standard weight attributes to categorize the relevance of the contents. The results show a significant growth in publications on artificial intelligence generative in education, especially from 2023, with emphasis on scientific articles about books. The United States leads in this field, especially in the development of chatbots and conversational applications for teaching. Although the authors are having a greater impact, there is an expansion into other disciplines such as medicine and engineering. Keyword and abstract analysis highlights the need to improve teacher training and infrastructure to optimize these tools. It is recommended to establish ethical and quality criteria for its academic application and consider the inclusion of preprints and recent works in future research.