Generative Artificial Intelligence (Generative AI) is becoming more widely recognised as a transformative technology that is reshaping the e-commerce landscape. This paper thoroughly examines Generative AI's role in e-commerce, including its historical evolution, core differentiators from traditional AI, emerging applications, implementation challenges, and future research directions. Generative AI allows for the creation of dynamic, context-relevant content, such as personalised product descriptions and targeted advertisements, as well as sophisticated visual and conversational experiences. E-commerce retailers are achieving unprecedented levels of personalisation and customer engagement using techniques such as generative adversarial networks (GANs) and multimodal transformer models. However, significant adoption barriers persist, including ethical concerns, legal complexities, consumer trust issues, resource constraints, and technological limitations. Addressing these issues necessitates transparency, strong governance, secure data practices, and scalable technology infrastructure. Finally, this paper identifies promising research directions, focussing on model explainability, reinforcement learning integration, privacy-preserving frameworks, and immersive technologies (AR, VR, metaverse). By synthesising existing scholarly literature, this review provides strategic insights for future research as well as practical implications, allowing academics and industry practitioners to effectively leverage Generative AI to foster innovation and competitive advantage in digital retail.
Khalil Israfilzade (Wed,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: