The search for technological solutions that can mitigate environmental impacts has become a global priority, driven by climate change challenges and the need for sustainable practices across economic sectors. The integration of artificial intelligence (AI) with green innovation represents a field of study that combines technological advancement with environmental sustainability, where AI serves as a catalyst for developing new technologies and processes that enhance energy efficiency, optimize resource utilization, and promote sustainable management systems. Universities play a fundamental role in this integration through sustainable education initiatives, serving as catalysts for developing AI-driven sustainability solutions while addressing challenges related to ethical considerations, technological barriers, and implementation complexities. The objective of this review is to map the relationship between green innovation and artificial intelligence (AI), analyzing the relevant scientific production in specialized journals. The adopted methodology followed a structured approach in stages. Initially, a search was conducted in the Web of Science and Scopus databases using a specific query that combined terms such as “Green Innovation”, “Artificial Intelligence”, “Machine Learning”, among others. The search was restricted to articles published from 2015 onwards, focusing on journals in the administration field. A total of 8065 articles were collected, which were analyzed through natural language processing (NLP) techniques, including n-grams and topic modeling, using Latent Dirichlet Allocation (LDA), to group the articles into different thematic categories. As a result, the articles address central themes related to sustainability, innovation, and digital transformation, with emphasis on areas such as supply chain management, sustainable development, and circular economy. The most cited article explores the potential of blockchain technology to improve sustainability in global supply chain management, addressing transparency and traceability challenges. The implementation of Sustainable Development Goals (SDGs) was also a highlighted theme, with proposals for transformations encompassing education, health, energy, sustainable cities, and the digital revolution. The structuring of topics through LDA modeling revealed five main thematic areas: (1) research in sustainability and emerging technologies; (2) technical approaches to problem solving; (3) how green innovation and environmental performance are shaping companies; (4) the role of companies in the sustainable development process; and, finally, (5) concern about the impact of climate change. These results show the growing importance of integration between AI and green innovation to face global environmental challenges, evidenced both in article citations and in the structure of identified topics.