Abstract

This systematic review compares the transformative impact of generative artificial intelligence (GAI) on retail business operations between 2020-2024. From a close analysis of 14 studies across six continents, the study identifies prevalent patterns of implementation, technology designs, and operation impacts of GAI adoption in retail settings. The work shows high potential for GAI in augmenting demand forecasting (with accuracy gains of up to 23%), optimizing inventory management (with a 17% reduction in carrying costs), and customer experience personalization (with conversion gains of 35%). The review identifies the prevalence of big language models, transformer models, and multimodal designs as the prevailing technological approaches, with varying success across retail types. Despite challenges of data quality, legacy system integration, and ethics, successful implementations by retailers show these challenges overcome with planning and organizational readiness. Analysis confirms GAI to be revolutionizing the business models in retail in revolutionary ways, with both operation efficiency and new strategic potential. A conceptual framework is presented that links GAI competencies to retail operational needs, implementation drivers, and value creation drives, with implications for researchers and practitioners in this technology-revolutionizing space.

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