Generative AI for Retail Innovation

Generative AI for Retail Innovation explores how emerging artificial intelligence technologies are reshaping the retail landscape by enabling smarter decision-making, personalized customer experiences, operational efficiency and sustainable business growth. The book focuses on the application of generative AI across retail functions, including marketing, customer engagement, merchandising, pricing, inventory management, supply chain operations, omnichannel retailing and strategic innovation. Readers will gain a comprehensive understanding of how retailers can leverage AI-driven capabilities to create value, enhance competitiveness and address evolving consumer expectations in a rapidly changing digital environment. The book is organized into fourteen chapters covering foundational concepts, theoretical perspectives, practical applications, industry case studies and future trends in AI-enabled retailing. Topics include AI-powered personalization, conversational commerce, recommendation systems, virtual shopping assistants, demand forecasting, intelligent supply chains, retail analytics, ethical and responsible AI adoption, sustainability, customer experience management and emerging innovations in smart commerce. Contributions from scholars and practitioners provide both academic rigor and real-world insights, offering readers a balanced perspective on the opportunities and challenges associated with implementing generative AI in retail. Key Features Interdisciplinary perspectives on AI applications in retail. Contemporary case studies, practical frameworks, evidence-based research findings and strategic recommendations for leveraging AI in retail environments. Structured content that integrates theory and practice while highlighting future directions for research and innovation. References in every chapter. Readership Primary Readership: Researchers, academicians, doctoral scholars and postgraduate students in marketing, retail management, business analytics, information systems and artificial intelligence. Secondary Readership: Retail managers, business leaders, consultants, entrepreneurs, technology professionals, policymakers and industry practitioners seeking to understand and implement AI-driven retail innovations.