AI investment is rising rapidly worldwide, yet its sustainability impact in emerging economies remains remarkably limited, a paradox that existing theories cannot fully explain. Despite widespread adoption of machine learning, predictive analytics, and automation tools, most firms in developing contexts struggle to convert AI capabilities into sustainability-oriented product innovation or circular business outcomes. To address this disconnect, this study proposes the AI–Product–Sustainability (AI–PS) Alignment Model, a conceptual framework that explains how AI capabilities drive product innovation that, in turn, strengthens sustainable business strategy within emerging-economy environments. Drawing on systematic literature review of 68 high-quality studies published between 2017 and 2022, this study synthesizes insights from AI adoption, innovation capability and sustainable business models. The findings show that AI capabilities enhance product development through improved design efficiency, eco-optimization, circularity-oriented features, and user-centric innovation processes. The study makes several novel contributions, including the development of the AI–PS Alignment Model and the theoretical integration of the Resource-Based View (RBV), Dynamic Capabilities Theory, Sustainable Business Model Innovation (SBMI) and Institutional Theory. It further reveals that institutional weaknesses such as infrastructure deficits, skill shortages, and regulatory ambiguity, significantly moderate the alignment between AI-enabled innovation and sustainability strategy in emerging economies. Therefore, this study provides a unified framework that clarifies how firms in emerging economies can strategically leverage AI to advance sustainable innovation and long-term competitiveness.