The pervasive utilization of data is crucial for adapting to new norms during disruptive crises. By integrating pervasive intelligence into socio-technical systems, automated adaptation and early-stage failure mitigation can be facilitated, fostering a cyber-physical intelligence continuum. Significant challenges arise in handling human-centered constraints and the extreme diversity of data. Traditional models struggle to incorporate behavioral dynamics, highlighting the need for novel AI-driven approaches for intelligent data fusion and utilization. This position paper discusses potential research directions at the intersection of data utilization, pervasive intelligence, and cyber-physical adaptation. Possible advancements in AI-driven mechanisms, edge intelligence, and distributed learning could help transform extreme data into actionable knowledge. The aim of this paper is to outline ideas that may contribute to enhancing data-driven adaptation and improving intelligent systems’ capacity to respond to real-world challenges.