The global polycrisis—an entanglement of environmental, economic, and institutional instabilities—has accelerated a crisis of care, characterized by the erosion of caregiving across personal, social, and educational domains. Nowhere is this crisis more acute than in Early Childhood Education and Care (ECEC), where neoliberal standardization, workforce precarity, and the separation of education from care have devalued relational, context-sensitive caregiving. This paper argues that the care crisis is not merely socio-political but epistemic and cognitive, reflecting a systemic failure to assign relevance to care within competing institutional and policy constraints. To address this, I introduce the Relevance Realization Framework for ECEC, drawing on cognitive science and artificial intelligence (AI) to reconceptualize care as a dynamic, adaptive process rather than a commodified service. By positioning care as an active, real-time negotiation of competing priorities supported—but not replaced—through AI tools designed to enhance professional caregiving judgment, this framework challenges rigid, outcome-driven models of early education. While offering a novel approach, I critically examine its trade-offs, including tensions between flexibility and standardization, risks of AI dependence, and structural limitations in policy reform. This study advances a scientific and interdisciplinary rethinking of care, proposing relevance realization as a foundational cognitive and systemic tool for reorienting ECEC in the face of increasing complexity.