AI is playing an increasing role in enhancing research efficiency and sustainability. University of New South Wales researchers employed machine learning to optimize green ammonia production catalysts, potentially revolutionizing fertilizer synthesis. Concurrently, integration of AI and hyperspectral sensors is advancing precise pesticide application, reducing chemical use. A University of Texas project utilizes AI-driven personalized messaging to boost physical activity in cancer survivors. Additionally, German research quantified environmental impacts of differing language-model AI prompts, underscoring ecological costs. These developments demonstrate AI's transformative potential across biotechnology and agricultural fields, balancing innovation with environmental considerations.