Rethinking e-business through AI: comparative insights and actionable solutions

Purpose The incremental adoption of artificial intelligence (AI) has been emphasized in much academic research and still remains incomplete with regards to the context-based acceptance and utilization. Prior studies mainly focused on technological acceptance and organizational growth but most of the time they overlook the constraints between economy-wise or country-wise differentiation in AI adaptation. To fill this gap, this paper adopts a comparative framework that integrates Technology Acceptance Model (TAM) & Dynamic Capability View (DCV) to analyze the dimension of AI adoption in e-business. Design/methodology/approach We adopt the systematic process of peer-reviewed articles within 2020–2025 to find the similarities and differences in adoption drivers across the developed and developing economies. Findings Findings reveal that TAM based factors like perceived usefulness and ease of use triggers user behavior and intention (high vs low adoption) in developed and emerging economies while the DCV factors such as sensing, seizing and reconfiguring are fully utilized by organization in developed countries where reconfiguration is obstructed in emerging economies because of resources, regulation and skills scarcity. Originality/value This study contributes by adopting a comparative framework with theoretical implication that not just explains the economic dimension in AI integrated e-business, rather provides a holistic idea of influence for user-level and organizational-level capability.