The integration of artificial intelligence (AI) in the fashion industry has brought about significant advancements, such as enhanced demand forecasting, streamlined inventory management, and personalized customer experiences. Despite these benefits, the adoption of AI also poses substantial environmental challenges, primarily due to its energy-intensive processes and associated electronic waste. This chapter explores the environmental impact of AI applications within fashion, with a focus on the energy demands of AI model training and inference, the carbon footprint of data centers, and the lifecycle of AI hardware. To address these challenges, the chapter examines strategies for adopting renewable energy sources—such as solar and wind power—to reduce the carbon footprint of AI operations. Additionally, it discusses advancements in algorithmic and hardware optimization aimed at improving energy efficiency. The chapter also emphasizes the importance of sustainable lifecycle management, including the proper disposal and recycling of electronic waste. Highlighted are successful implementations of sustainable AI practices through case studies from leading fashion brands like Nike and academic research. The chapter concludes with policy recommendations and future directions to align AI-driven innovation with environmental sustainability goals. This comprehensive examination aims to balance technological advancement with ecological responsibility, ensuring that AI’s role in fashion contributes positively to environmental sustainability.