This chapter briefly discusses expert systems such as Artificial Intelligence (AI) and machine learning (ML) concepts, deliberating on the overlap between the three research communities around ICTs for sustainable development, pointing to the difficulty in defining and measuring sustainability. The interdisciplinary nature of research around AI and ML for sustainable development, mainly in the areas of climate, conservation, and other environmental subjects, is introduced. Ensuring that data, technology, and knowledge derived through AI and ML practices contribute to improving human and environmental quality of life and the ability to promote sustainability becomes extremely relevant to ensure the scientific and democratic development in the use of technologies for planetary well-being. Artificial intelligence and machine learning are complex, interdisciplinary fields that are constantly evolving. AI is generally defined as the ability to create machines that can think and act intelligently, accepting as true that any substantive subject refers to the capacity of a computer or computer-controlled robot to perform tasks that correspond to the characteristics of human beings. With a similar perspective, the father of AI points out that AI is the science and engineering for making intelligent machines, especially intelligent computer programs. To better understand the term machine learning, one can look at similar conceptual levels. It is a type of AI that provides computers with the ability to learn during execution, based on data provided and without direct action of a programmer, allowing the construction of predictive mathematical models for solving problems characterized by the data, creating simulations, and controlling computer systems.