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The integration of artificial intelligence (AI) into strategic management has transformed how organizations design decision systems and pursue competitive advantage in digital environments. This narrative literature review synthesizes peer-reviewed studies, focusing on AI-enabled strategic decision-making, algorithmic organizational systems, and the mechanisms through which AI generates sustained performance gains. Drawing on top-tier journals such as Strategic Management Journal, MIS Quarterly, and Technological Forecasting and Social Change, the analysis identifies recurring patterns of augmentation rather than replacement. It surfaces persistent tensions in human–AI collaboration and governance. Key findings show that AI augments predictive accuracy and resource allocation, yet introduces novel risks related to algorithmic bias, ethical oversight, and the erosion of traditional sources of advantage. The review traces the field’s evolution from early conceptual explorations of human–AI symbiosis to more recent examinations of generative AI’s disruptive potential and firm-level outcomes. Conceptual overlaps emerge around the centrality of hybrid decision architectures, while inconsistencies appear in assessments of long-term competitive sustainability. By mapping these streams and their interrelationships, the manuscript offers a structured foundation for understanding AI’s strategic role. It highlights critical gaps in cross-industry generalizability, ethical frameworks, and the interplay between technological affordances and organizational adaptation. This synthesis equips scholars and executives with an integrated lens on how AI is reconfiguring strategic management in the digital age.

Platform-based business models have become central to digital competition because they reorganise how firms create, coordinate, and appropriate value across multi-sided ecosystems. Unlike traditional pipeline models, platforms depend on interactions among users, complementors, developers, advertisers, and other external actors. This shift has made platform competitiveness a strategic phenomenon that cannot be explained only by internal resources or product-market positioning. This systematic review examines how platform-based business models generate and sustain firm competitiveness through three interrelated mechanisms: network effects, ecosystem governance, and value capture. The objective is to synthesise fragmented evidence from strategy, information systems, innovation, and management research. The review focuses on how these mechanisms operate individually and how their interaction shapes platform performance and durability. The findings show that platform competitiveness is supported by architectural design, multi-sided participation, network effects, ecosystem orchestration, and monetization choices. However, the evidence also reveals tensions between openness and control, growth and quality, value creation and value capture, and network expansion and strategic vulnerability. Five tables summarise the review method, platform typology, network effects, governance mechanisms, and value capture models. The review concludes that platform competitiveness should be understood as a dynamic system rather than as the automatic result of scale. Network effects require governance, governance shapes value capture, and value capture can either strengthen or weaken ecosystem health. Future research should therefore examine platform success and failure through longitudinal, comparative, and context-sensitive designs.