Artificial Intelligence Business Models: A Narrative Review of the Literature and Implications for Value Theory and Technology Governance

Artificial intelligence (AI) is increasingly treated not only as a tool within firms but as a force that reshapes how firms create, deliver, and capture value. This narrative review synthesizes peer-reviewed and preprint scholarship on AI business models, drawing on a bibliometric-systematic review of 87 management articles, a taxonomy of AI startup business models, case-based studies of AI-enabled business model innovation in industrial ecosystems, theory on data network effects, and recent work on generative AI and foundation models. Four conclusions emerge. First, AI business model research rests on established business model and innovation theory rather than on a distinct theoretical base. Second, scholars have mapped how AI creates value more thoroughly than how firms capture it. Third, data, platforms, and ecosystems recur as the mechanisms that distinguish AI-based models from earlier IT-based ones. Fourth, the foundation model era raises new strategic questions about openness, lock-in, and value chain structure that empirical research has barely begun to test. The review closes with a research agenda organized around a single stratified inquiry into the structural conditions of value capture under foundation-model regimes, with particular attention to creative and design-led industries and the role of governance.