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In an era of rapid digital transformation, organizations confront a fundamental tension: algorithmic systems excel at pattern recognition and predictive efficiency, yet falter when confronted with ambiguity, ethical nuance, and contextual idiosyncrasy. This theory-development article advances a novel conceptualization of organizational intelligence as an emergent property of deliberate integration between human judgment and computational insight. Synthesizing recent scholarship on human–AI collaboration, hybrid decision systems, and the limits of automation, the article argues that digitally transformed firms achieve superior strategic outcomes only when they architect “augmented organizational intelligence”—a hybrid capability that transcends both pure human intuition and standalone machine intelligence. The proposed framework delineates cognitive complementarities, identifies boundary conditions of algorithmic autonomy, and specifies integration mechanisms that enable dynamic synthesis. Five core propositions articulate causal pathways through which human oversight, interpretive layering, and feedback loops convert raw computational output into contextually enriched organizational decisions. By bridging literatures from strategic management, information systems, and organization science, the article offers a conceptual architecture for hybrid intelligence that addresses persistent gaps in understanding how firms can move beyond technology adoption toward genuine cognitive augmentation. Theoretical and managerial implications underscore the need to redesign decision architectures to preserve human agency while harnessing machine scalability, thereby redefining organizational intelligence for the post-digital age.