Artificial intelligence (AI) is transforming e-business globally, yet its adoption in emerging markets poses distinct challenges. This paper examines AI integration strategies within e-commerce in developing economies, focusing on South Africa’s Takealot as a core case study. We compare Takealot’s approach to those of global leaders Amazon and Alibaba, and regional peer Jumia, to identify how AI can be effectively adopted under infrastructure constraints, regulatory frameworks, and diverse consumer contexts. We propose a novel framework, ADAPT (Assessment, Development, Adaptation, Phased implementation, Tracking), tailored to guide AI adoption in emerging market e-commerce. Through a literature review and comparative analysis, we demonstrate how Takealot’s measured, context-aware adoption of AI aligns with best practices and addresses local barriers. The ADAPT framework and accompanying principles (contextual intelligence, infrastructure-aware design, gradual capability building, trust-centric implementation, and localized metrics) provide actionable guidance for e-business platforms in similar markets. Our findings underscore that successful AI deployment in developing economies requires not a direct transplantation of solutions from mature markets, but rather strategic adaptation to local conditions. The paper’s contributions include a structured framework for AI adoption in resource-constrained e-commerce environments and insights bridging global AI innovations with emerging market needs.