Radiology significantly contributes to the environmental footprint of healthcare, owing to the energy-intensive manufacturing and use of imaging equipment. The healthcare sector is responsible for 5–10% of greenhouse gas emissions in developed nations, with medical imaging accounting for about 1% of global emissions. Imaging devices like MRI, CT, and ultrasound vary in their energy consumption, with MRI machines being the most energy-intensive. Notably, much of the energy expenditure from medical imaging occurs during times when equipment is not actively in use. AI offers promising efficiency gains that could reduce emissions in radiology by optimizing operational requirements and promoting sustainability. Despite its potential to increase data storage and computational energy needs, AI can help achieve a net reduction in emissions. This chapter examines the environmental impact of radiology and discusses AI’s role in mitigating this footprint while enhancing healthcare delivery.