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The proliferation of digital connectivity has repositioned data networks as central infrastructures for knowledge exchange in contemporary organizations. Traditional models of organizational learning and strategic capability development, rooted in hierarchical or localized processes, are increasingly insufficient to explain how knowledge flows across distributed digital systems. This theory-development article synthesizes evidence from recent scholarship to argue that data networks do not merely channel information but actively reshape learning dynamics and capability formation through real-time integration, boundary-spanning collaboration, and human-machine coordination. By examining digital knowledge networks, data-driven knowledge sharing, and knowledge integration in digital ecosystems, the study identifies critical mechanisms that accelerate absorptive capacity and enable adaptive strategic capabilities. Six original theoretical propositions are advanced to explain these transformations: data networks enhance knowledge fluidity, foster emergent collective learning, facilitate cross-boundary integration, amplify analytics-enabled capability building, moderate the effects of environmental dynamism on learning, and generate new organizational learning cultures. The proposed framework contributes to digital business and management studies by offering a unified theoretical lens that bridges knowledge management, organizational learning, and strategic capability literatures. Implications extend to both theory and practice, underscoring the need for organizations to deliberately orchestrate data infrastructures. Future research directions emphasize longitudinal and multi-level investigations of these digitally mediated processes.