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The rapid integration of artificial intelligence and algorithmic systems into core organizational processes has transformed decision-making, yet it has simultaneously exposed critical deficiencies in traditional corporate governance mechanisms. Algorithmically mediated organizations now confront unique challenges in maintaining accountability for opaque automated decisions, ensuring transparency in high-stakes outcomes, and exercising strategic oversight amid rapid technological evolution. This conceptual manuscript synthesizes contemporary scholarship to map these tensions and introduces the SOAR Framework—Strategic Oversight for Algorithmic Responsibility—as a novel multi-layered governance architecture. Developed through a systematic review of peer-reviewed sources, the framework comprises six interdependent layers: the algorithmic decision core, transparency and explainability systems, accountability assignment protocols, strategic oversight bodies, risk and compliance shields, and adaptive feedback loops. By embedding human-AI hybrid controls and continuous audit mechanisms, SOAR enables organizations to align algorithmic mediation with ethical, legal, and strategic imperatives. The model addresses pressing gaps identified in existing literature, including the diffusion of responsibility in AI-driven environments and the insufficiency of conventional board-level oversight. Contributions to digital business and management studies include a practical blueprint for implementation and a conceptual foundation for future empirical testing. Ultimately, the SOAR Framework equips corporate leaders to govern algorithmic systems responsibly while preserving competitive advantage in digitally transformed enterprises.