The Paradox of Artificial Intelligence and Sustainable Entrepreneurship: A Bibliometric Analysis

Abstract

This study investigates the complex relationship between artificial intelligence (AI) and sustainability, addressing the dual potential of AI to enhance sustainable practices while also presenting significant environmental challenges. To comprehensively understand these dynamics, an approach combining systematic literature review with quantitative analyses based on Web of Science (WoS) data was adopted; VOSviewer (version 1.6.20) software was utilized for bibliometric mapping. This methodology facilitated the examination of AI applications across various sectors, focusing specifically on their role in enhancing resource efficiency, optimizing energy management, and supporting decision-making processes aligned with the United Nations Sustainable Development Goals (SDGs). The findings reveal a paradox inherent in the deployment of AI technologies: while AI possesses the capacity to drive efficiencies and stimulate innovations in fields such as energy management, agriculture, and waste management, it concurrently contributes to substantial carbon footprints and energy consumption associated with its operational infrastructure. Particularly, the energy demands for training and maintaining AI systems, especially those reliant on non-renewable energy sources, raise critical concerns regarding their ecological sustainability. This phenomenon, often referred to as "Red AI," illustrates how the promise of AI in fostering sustainable outcomes can be undermined by the environmental costs of its implementation. Key ethical considerations also emerged prominently in the study, particularly concerning algorithmic biases and the risk of exacerbating existing inequalities when AI systems are applied without adequate oversight. Therefore, the research advocates for the development of "Sustainable AI" frameworks that integrate environmental responsibility and social equity into the design, deployment, and lifecycle management of AI, emphasizing that such frameworks must ensure ethical standards and sustainability goals alongside AI's technological benefits. In conclusion, stakeholders—including technologists, policymakers, and ethicists—must engage in collaborative efforts to reconcile the benefits of AI with its ecological impacts; adopt a responsible innovation approach prioritizing fairness, inclusivity, and environmental stewardship; and establish robust regulatory frameworks that guide the development and implementation of AI systems towards sustainable outcomes. By addressing these challenges proactively, AI holds significant potential to serve as a powerful tool in achieving meaningful progress towards global sustainability objectives.