Artificial Intelligence in Green Marketing: A Systematic Literature Review

Abstract

As environmental sustainability pressures intensify and AI technologies rapidly evolve, the integration of AI into green marketing strategies has become increasingly prominent. This systematic review examines the application of artificial intelligence (AI) in green marketing, with a focus on studies published between 2020 and 2024. This review addresses two key research questions: the effectiveness of different types of artificial intelligence in green marketing applications, and the role of AI in supporting enterprise development in this context. A comprehensive search of SpringerLink, Web of Science, and Google Scholar initially identified 200 records. After duplicate removal and multi-stage screening, 47 articles were deemed to meet the inclusion criteria. Only peer-reviewed journal articles in English were included. Study quality was appraised using established evaluation criteria to ensure methodological rigor. Among these, Thinking AI, Mechanical AI and Feeling AI appeared in 45 studies, 23 studies and 15 studies, respectively. The selected studies span 34 journals and 28 countries, reflecting both the rising academic interest and the interdisciplinary character of this emerging field. However, this review also identifies notable deficiencies in the current body of work. This review integrates these AI types with the 4Ps framework to form a concise conceptual mapping of their respective functions. Although AI has been positioned as a powerful driver of green marketing, research remains fragmented, with limited assessment of AI’s sustainability, weak data and ethical safeguards, and insufficient long-term and global perspectives. This underscores the need for a deeper and more systematic understanding of AI to better achieve the goals of green marketing and improve its practices.