AI and environmental sustainability are an exciting frontier to improve the health of populations, especially for NTDs and other infectious diseases. The concept of green health highlights how AI technologies are to be used when it comes to disease diagnosing or preventing it and make the ecosystem sustainable for the betterment of human beings. With emerging global crises in health and environment, AI provides opportunities for sustainable change in healthcare systems keeping ecosystem- oriented approach. AI has proved its versatility in multiple connection of healthcare; from diagnostics to prediction and even personalized treatments. Using AI in analyzing the information relating to environment helps the healthcare systems to make better decisions in resource management, enhance the disease monitoring and control as well as disease early identification in case of an outbreak. For instance, AI patterns can be employed to study satellites images and climate data to identify possible occurrences of vector-borne illnesses in given areas to control harm before incidents go out of hand and become public health threats. Artificial intelligence can have applications in diagnostic tests utilizing machine learning, computational vision and natural language processing to detect diseases in their early stage thus decrease the prevalence of infections cases as well as possible fatality in future due to the enhanced treatment procedures and lower healthcare expenditure. It describes how satellite and IoT, together with environment sensors, can track and report on zoonotic diseases, air quality and water pollution and thus link environmental and public health surveillance. AI integrated biomedical waste management systems can be highly effective for major improvements in the segregation and disposal of the wastes that results in the decline of the ecological impact of the healthcare organizations. However, there is still a problem of how to provide equal opportunities for using AI technologies for all populations. Eliminating these disparities will mean that decision makers, data scientists, and health care professionals must be willing to expend resources to build the physical and organizational foundation necessary for effective AI to be deployed in these populations. Also, the issue of ethical use of collected data, and the potential of AI in reflecting or enhancing bias must be addressed to guarantee that any AI application is created and implemented safely. The proposed approach of integrating appropriate technology with ecological imperatives can result in the co-development of sustainable healthcare systems for better health and a better environment. Such an inclusive approach is considered crucial in the advancement of global health policies toward a healthy planet in the future.