Artificial Intelligence-Driven Technologies for Environmental Sustainability in the Healthcare Industry

This chapter broadly focuses on the state of artificial intelligenceArtificial intelligence (AI) in environmental sustainabilityEnvironmental sustainability in the healthcare sector. It also explores different AI technologies for analysing the efficient use of resources, waste minimisation, and improving the overall organisational operation by explaining the risks of ethical issues and potential regulation. A systematic literature review (SLR) was performed according to the Preferred Reporting Items for Systematic Reviews and the Population-Intervention-Comparison-Outcome (PICO) model to search for papers on AI-driven technologies in healthcare sustainabilitySustainability. Accordingly, forty-one (41) studies were considered as the study's sample. The findings accentuated the collaboration of AI with blockchain, IoT, and other advancements to study the effect of the resulting solutions on energy consumption, waste treatment, and ecological tracking. Several examples are used in the study: energy consumption forecasting using AI, biomedical waste management through deep learning, and policy analysis based on natural language processing. The findings further revealed that AI-integrated blockchain improved transparency and accountability by creating a tracking system in the supply chain and carbon credit system. The chapter also outlines some of the risks inherent in the deployment of AI in healthcare, including data privacy issues, algorithm bias, and energy concerns about the use of AI in healthcare. The study’s results imply that AI can significantly impact healthcare facilities’ environmental impact and upgrade efficiency and sustainabilitySustainability work. We encourage government authorities to call for creating more responsive regulations and incentives to integrate AI technologies in healthcare. The chapter also emphasises the importance of a multidisciplinary approach with researchers, technologists, and clinicians to optimise the roles of AI for sustainabilitySustainability.