Sustainability and Artificial Intelligence: Necessary, Challenging, and Promising Intersections

A comprehensive bibliometric study analyzing 541 research papers from Web of Science reveals how artificial intelligence and sustainability research intersect across complex, interconnected environmental, social, and governance challenges. The research maps necessary, challenging, and promising areas where AI can address sustainable development while highlighting the need to diversify the community of practice and expand AI applications across institutions.

This bibliometric analysis addresses a critical gap in understanding how AI technologies intersect with sustainability imperatives. The research synthesizes 541 academic papers to identify patterns in how the AI and sustainability communities are engaging with shared challenges, revealing that both fields increasingly recognize each other as essential to solving complex, dynamic problems. The convergence represents a maturation of both disciplines beyond siloed research into integrated frameworks that acknowledge environmental and social dimensions of technological development.

The significance of this work lies in its systematic documentation of emerging research trends rather than breakthrough discoveries. As AI deployment accelerates globally, understanding its sustainability implications becomes foundational for responsible development. The study identifies that green and sustainable technology research serves as a bridge across multiple academic disciplines, suggesting institutional frameworks are evolving to support interdisciplinary collaboration.

For technology developers and organizations, the findings indicate increasing scrutiny of AI's environmental footprint and social governance implications. This shapes investment priorities and regulatory expectations around AI development. Companies building AI systems face growing pressure to demonstrate sustainability credentials, affecting everything from energy consumption monitoring to training dataset ethics. The research suggests this trend will intensify as institutional awareness grows.

Moving forward, the article highlights the need to expand participation in AI-for-sustainability research beyond academia into corporate research labs, policy institutions, and developing economies. The identification of underrepresented application areas suggests opportunities for innovation where sustainability and AI solutions remain unexplored, particularly in emerging markets where AI could address unique environmental challenges.

• →AI and sustainability research converge on addressing complex, interconnected, dynamic problems requiring interdisciplinary approaches.
• →Bibliometric analysis of 541 papers reveals green and sustainable technology as a key bridge across academic disciplines.
• →Growing institutional recognition of AI's environmental and social governance implications shapes development priorities.
• →Significant research gaps exist in specific application areas and developing economy contexts for AI-enabled sustainability solutions.
• →Expanding the community of practice requires involvement from corporate labs, policy institutions, and non-Western research centers.