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A significant number and range of challenges besetting sustainability can be traced to the actions and interactions of multiple autonomous agents (people mostly) and the entities they create (e.g., institutions, policies, social network) in the corresponding social-environmental systems (SES). To address these challenges, we need to understand decisions made and actions taken by agents, the outcomes of their actions, including the feedbacks on the corresponding agents and environment. The science of complex adaptive systems—CAS science—has a significant potential to handle such challenges. We address the advantages of CAS science for sustainability by identifying the key elements and challenges in sustainability science, the generic features of CAS, and the key advances and challenges in modeling CAS. Artificial intelligence and data science combined with agent-based modeling promise to improve understanding of agents’ behaviors, detect SES structures, and formulate SES mechanisms.