Search

Generative artificial intelligence has emerged as a transformative force in business and management, fundamentally altering how organizations create value, make decisions, and manage knowledge. This narrative review synthesizes contemporary scholarship to examine how generative AI functions as a new layer of organizational capability, creating strategic opportunities while simultaneously introducing significant managerial, ethical, and governance challenges. The analysis reveals that generative AI differs fundamentally from prior forms of artificial intelligence through its capacity for content generation, contextual reasoning, and human-like interaction, enabling unprecedented applications in innovation management, strategic decision support, knowledge work transformation, and business model experimentation. However, these capabilities generate corresponding vulnerabilities, including algorithmic hallucination, embedded bias, operational opacity, and organizational over-dependence. The review identifies three major tensions: augmentation versus automation, efficiency versus reliability, and innovation acceleration versus governance lag. Drawing on scholarly sources, this article proposes an integrative framework situating governance and human oversight as essential mediating mechanisms between generative AI capabilities and organizational outcomes. The findings suggest that successful generative AI adoption requires organizations to balance opportunity exploitation with risk mitigation through structured accountability systems, human-in-the-loop protocols, and adaptive governance architectures.