The Sustainability Paradox of Artificial Intelligence: How AI Both Saves and Challenges Resource Management Efforts

Abstract

The net gain of AI and sustainable development remains a critical area of inquiry, as Artificial Intelligence (AI) offers opportunities and challenges in advancing sustainability. AI offers benefits like optimized energy use and improved resource efficiency, but its rapid adoption also results in high energy consumption, increased e-waste, and resource depletion. This contradiction is referred to as the Sustainability Paradox and calls for a structured evaluation of AI's impact. The Sustainable AI Impact Assessment Framework (SAIAF) serves as a tool to measure AI's role in sustainability while accounting for its unintended consequences. It assesses AI across three dimensions: environmental (carbon footprint, energy use), social (labor market changes, ethical issues), and economic (cost efficiency, long-term resilience). Case studies in precision agriculture and smart energy grids demonstrate how SAIAF aids policymakers and industries in minimizing negative impacts while enhancing the sustainability gains of AI. However, fragmented global policies complicate the effective implementation of AI for sustainability, leading to inconsistent regulations and misaligned objectives. This paper highlights the importance of cohesive AI governance and shared sustainability standards. By incorporating SAIAF into policies and industry practices, AI can shift from being resourceheavy to becoming a strategic sustainability ally. The study suggests further research on the sustainability of AI lifecycles, adaptive policies, and innovations in energy-efficient AI systems for a more balanced and responsible future.

Keywords: Sustainable AI, Energy-Efficient AI, AI Impact Assessment, AI and Circular Economy, AI and Environment