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Algorithmically mediated markets now dominate data-driven industries, where visibility, pricing, ranking, and resource allocation are governed by opaque automated systems rather than direct human negotiation. This theory-development article synthesizes peer-reviewed studies to advance a novel conceptual explanation of strategic risk—the emergent, self-reinforcing exposure arising from the interplay of uncertainty, dependence on algorithmic intermediaries, and competitive volatility. Traditional strategy frameworks fail to capture how platform ecosystems invert firm boundaries, how algorithmic opacity exacerbates information asymmetry, and how automated feedback loops accelerate market instability. We argue that strategic risk is not merely an external shock but a systemic property generated by algorithmic governance itself. Dependence on digital infrastructures locks organizations into structural vulnerabilities, while rapid changes in recommendation and ranking algorithms create unpredictable volatility that propagates across ecosystems. The article develops six theoretical propositions that delineate causal pathways from algorithmic mediation to heightened risk exposure and identifies organizational responses that may either mitigate or inadvertently amplify instability. A conceptual model visualizes these dynamics, highlighting directional flows and reinforcing feedback loops. By reframing strategic risk as endogenous to algorithmically governed markets, the framework offers new avenues for digital business and strategy theory, emphasizing the need for algorithmic resilience capabilities. Practical implications underscore the limits of conventional risk management in platform-dominated environments.

Digital businesses operate in an environment where competitive advantage increasingly depends on the ability to respond to technological disruption, shifting customer expectations, ecosystem instability, cyber threats, and operational shocks. Resilience in this context cannot be reduced to recovery after disruption, because digital firms must also anticipate risk, adapt strategically, and preserve continuity across interdependent technological and organizational systems. Existing resilience frameworks remain fragmented. Some emphasize agility and dynamic capability development, while others focus on cybersecurity, platform strategy, business continuity, or organizational learning as separate domains. This fragmentation limits understanding of how digital businesses actually withstand disruption when market responsiveness, platform dependence, cyber exposure, and learning capacity interact simultaneously. This article develops the Digital Business Resilience Framework as an original conceptual framework for explaining resilience in digital business. The framework integrates four co-equal pillars: strategic agility, platform dependence awareness, cyber risk management, and organizational learning. It argues that resilience emerges when these pillars mutually reinforce one another rather than when they are managed as isolated capabilities. The framework contributes to digital business and resilience scholarship by shifting attention from isolated adaptive responses to systemic resilience architecture. It also offers managers a diagnostic lens for identifying weak points in digital business resilience and for designing integrated practices that connect agility, platform governance, cyber preparedness, and learning routines.