Applications of Generative Artificial Intelligence in Management and Business: An Integrative Review and Future Research Agenda

Generative artificial intelligence (GenAI) has rapidly moved from a novel technical phenomenon to a practical business capability that is reshaping managerial work, customer interaction, innovation, platform ecosystems, and inter-organizational coordination. Large language models, diffusion models, multimodal systems, conversational agents, virtual assistants, and code generation tools are now used in marketing, customer service, tourism, human resource management, software development, supply chain management, business model innovation, entrepreneurship, and sustainability communication. Yet the management and business literature remains fragmented across information systems, marketing, consumer behavior, operations, strategy, HRM, entrepreneurship, innovation, and ethics. This integrative review synthesizes ۴۵ unique academic sources to clarify where GenAI is being applied, how it creates value, and what risks require managerial governance. The review organizes the literature into nine application domains: strategy and business model innovation; innovation and product development; marketing, advertising, and consumer behavior; customer service, conversational commerce, and tourism; HRM and workforce transformation; knowledge work and software development; digital platforms and ecosystems; operations and supply chain management; and entrepreneurship, SMEs, and sustainability. Across these domains, GenAI creates value through automation, augmentation, insight generation, personalization, knowledge transfer, co-creation, democratization, coordination, adaptation, and ecosystem orchestration. At the same time, it creates risks related to hallucination, bias, privacy, intellectual property, algorithm aversion, authenticity, deception, customer trust, deskilling, hidden labor, and environmental impact. The article develops an integrative framework linking GenAI inputs, value mechanisms, application domains, business outcomes, contextual moderators, and governance controls. It concludes with managerial implications and a future research agenda for responsible, human-centered, and strategically aligned GenAI adoption in business.

کلیدواژه ها:

Generative artificial intelligence ، Management ، Business model innovation ، Marketing ، Consumer behavior ، Supply chain management ، Human-AI collaboration ، Responsible AI