Strategic Integration of Generative AI in Organizational Settings: Applications, Challenges and Adoption Requirements

Generative AI is revolutionizing the way organizations operate, offering transformative capabilities that span automated content creation, strategic decision-making, and customer engagement through AI-driven chatbots. This paper conducts a comprehensive literature review to explore the applications, challenges, and strategic requirements for adopting generative AI in organizational contexts, focusing on the distinct needs of Small and Medium Enterprises (SMEs) and large organizations. The findings reveal that generative AI can improve efficiency, drive innovation, and improve customer satisfaction, but its adoption pathways differ significantly between organizational sizes. For SMEs, the emphasis lies on cost-effective and scalable solutions that optimize resource-constrained operations. At the same time, large organizations leverage their extensive resources to scale AI applications, manage complex systems, and address ethical and regulatory challenges. The study highlights critical barriers, including data privacy concerns, integration with legacy systems, and resistance to change, alongside actionable recommendations for overcoming these challenges. By synthesizing insights from 38 high-quality studies, this research bridges the gap between theory and practice. It provides a roadmap for organizations of varying scales to harness generative AI as a cornerstone of their digital transformation journey. It also identifies key areas for future exploration, ensuring relevance in this rapidly evolving field.