This study explores the significance of individual learning in the context of sustainability transitions and examines the possibilities of augmenting human capabilities with artificial intelligence (AI). Looking beyond the predominant collective learning focus, this study presents an integrative literature review that elucidates the underlying factors (paradigm, learning needs, and competencies) and mechanisms (multilevel situational mechanisms; action formation mechanism of the combinatory learning process; and transformational mechanisms of evolutionary and relational nature) that influence the process and role of individual learning in the multilevel embedded context of sustainability transitions. A conceptual framework is developed to discuss the human-centric alignment of AI with these elements. The analysis identifies key points where AI can synergistically enhance the learning process, particularly in the restructuring of learning spaces and the facilitation of learning approaches that improve competency development. Conversely, potential risks are identified in the fitting management of the decentralized application of AI into learning processes, necessitating AI literacy to result in empowered agency. The results highlight the imperative to thoughtfully navigate the creation of human–AI-empowered learning systems by leveraging both systemic and individual perspectives for transparency for the optimized alignment of roles and responsibilities between humans and AI in the creation of an improved learning function necessary to steer sustainability transitions.