Charting the Evolution of Generative Artificial Intelligence: Insights from A Systematic Literature Review

Abstract

In this systematic literature review, we aimed to identify and thoroughly analyze the existing scientific knowledge related to a notably emerging field of generative AI. In strict adherence to the SPAR-4-SLR protocol, we focus on 1,104 peer-reviewed articles from the Scopus database, published between 2015 and 2025. Using bibliometric and thematic mapping methods, we address two main research questions: the first concerns the major publication trends in GenAI research, and the second deals with the intellectual structures and thematic domains shaping the field. Our results indicate an abrupt increase in scientific production since 2022, a consequence of the launch of models such as GPT, DALL·E, and Stable Diffusion, which are becoming increasingly powerful. We further identify five main research clusters: the technological foundations of generative AI, where researchers focus on building and utilizing LLMs and deep learning; professional and educational applications; ethical and governance issues; AI-assisted creativity; and user perceptions. Additionally, we find that higher education plays a significant role in the area, both in the application of ideas and the exploration of relevant questions. This review highlights the field's strong interdisciplinary character and, at the same time, reveals the current challenges that the sector faces. We outline a systematic research program to guide further studies of the implementation, impact, and problems of GenAI in enterprises and communities.