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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.

In an era of pervasive digitalization, organizations possess unprecedented volumes of data, yet few convert these resources into enduring strategic capabilities that deliver sustainable competitive advantage. This conceptual article synthesizes the literature on data as a strategic resource, information processing, analytics-enabled decision-making, and organizational knowledge conversion to address a critical gap: the mechanisms by which raw data become higher-order capabilities. Drawing on studies, the article introduces the Transforming Information into Strategic Capability Architecture (TISCA) framework. This novel six-layer model explicates the progressive transformation from data possession to capability orchestration and performance reinforcement. The framework highlights the pivotal roles of digital infrastructures, analytics systems, organizational sensemaking, and dynamic feedback loops in turning information into a source of sustainable advantage. By mapping the processes of acquisition, interpretation, integration, deployment, realization, and reinforcement, TISCA offers managers and scholars a practical architecture for designing data-driven capability-building initiatives. Theoretical contributions extend the resource-based view and dynamic capabilities literature by specifying the micro-processes of information-to-capability conversion. Managerial implications focus on the organizational conditions required for information resources to generate long-term competitive differentiation rather than transient operational gains.