Artificial Intelligence as a Catalyst for Business Sustainability: A Bibliometric Analysis of Its Impact on Business Model Optimization

Abstract

This analysis delves into the strategic crossroads of artificial intelligence (AI) and the transition toward sustainable business models, an increasingly urgent challenge. With the triple pressure of the climate crisis, tightening regulations, and constantly evolving consumer awareness, an inevitable question arises: what is AI's real role in all of this? The main problem is not the lack of technology, but the lack of a clear roadmap to organize all the scientific knowledge about this convergence. It's like having a state-of-the-art navigation system without knowing where it's going. To map this emerging territory, we used a quantitative, exploratory, and retrospective bibliometric approach using databases such as Scopus. We reviewed 216 publications between 2019-025 and used tools such as VOSviewer and the Bibliometrix package in R to conduct our analysis. This setup helped us identify co-authorship networks, institutional collaborations, and, above all, the thematic clusters that define the field. Our findings show a sharp increase in scientific output after 2020, with journals such as the Journal of Cleaner Production and IEEE Access serving as key platforms. Thematic clusters reveal that AI acts as a digital nervous system for businesses: driving energy efficiency, performing predictive analytics for risk management, and optimizing supply chains.