The development and adoption of Artificial Intelligence (AI) technologies has driven a significant increase in energy consumption, raising concerns about their environmental impact. This paper presents a comprehensive framework for assessing the sustainability of AI tasks through a measure of \({\textrm{CO}}_2\) equivalent ( \({\textrm{CO}}_2\) e) emissions. By analyzing key factors such as computational power, hardware efficiency, cooling systems, energy provider mix, and geographic location, we propose an equation that estimates the environmental cost of AI operations. Our approach aims to balance technological progress with environmental responsibility by providing a systematic method to assess and mitigate the carbon footprint of AI systems. Experimental results demonstrate the practical application of the proposed model in real-world scenarios, highlighting the trade-offs between model performance and sustainability. This study serves as a call to action for responsible AI development, emphasizing the importance of integrating sustainability into the core design and deployment of AI technologies.
