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

Jonathan R.-F.S. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2025) · DOI: 10.18687/leird2025.1.1.125

Resumen

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 and Web of Science. We reviewed 216 publications between 2019 and 2025 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. Furthermore, evidence suggests that the value of AI goes far beyond basic optimization. The true turning point will come when we stop using AI only to refine our current models and start leveraging it to completely reinvent the way we do business. © LEIRD 2025.All rights reserved.

Instituciones: Universidad Autónoma del Perú