The Dual-Edged Sword of Automation: Assessing the Role of Artificial Intelligence in Accelerating and Inhibiting Sustainable Development

Abstract Artificial Intelligence (AI) has emerged as a fundamental catalyst for transformation across global societies, fundamentally altering the pathways available to achieve the United Nations Sustainable Development Goals (SDGs). This paper presents a critical, socio-technical review of AI's dual role as both an enabler and an inhibitor of sustainability. Synthesizing recent macro-level consensus frameworks and empirical case studies, we demonstrate that while machine learning architectures optimize resource efficiency, power smart grids, and augment climate tracking, they simultaneously expose systemic vulnerabilities. These include severe ecological footprints driven by the energy-water nexus of hyperscale data centers, algorithmic bias that exacerbates socio-economic inequality, and a compounding interdisciplinary 'expertise gap.' This paper maps these dual-impact nodes across environmental, social, and economic dimensions, concluding with actionable governance strategies designed to guide policy toward a balanced digital-green transition.