Materials in extreme environments present numerous research challenges, in particular the prevalence of costly and time-consuming experiments and computational models that offer only sparse data for materials design decisions. The Center on Artificial Intelligence for Materials in Extreme Environments (CAIMEE) provides a focus for research activities that overcome these barriers through integrative robotic automation, novel high-throughput experimentation, machine learning (ML)-accelerated computational models and, artificial intelligence (AI)-/data-driven design iterations that will enable developing materials with tailored properties for sustainable performance in extreme environments. CAIMEE is developing and implementing AI and machine learning tools to evaluate materials and make actionable design decisions in the context of an automated system. Bringing together researchers, both at Johns Hopkins University and externally, who share an interest in AI-assisted analysis and design of materials for extreme conditions, CAIMEE will enhance the institutional capabilities to address problems of critical relevance to federal agencies including the Department of Defense, Department of Energy and National Aeronautics and Space Administration, among others. CAIMEE resides within the Hopkins Extreme Materials Institute (HEMI) located on the Homewood campus of Johns Hopkins University.