Innovation Management in the Age of Generative AI: Strategic Challenges and Opportunities for Business Leaders
Abstract
Generative artificial intelligence (GenAI) is a transformative shift in how organizations can navigate innovation processes and stay competitive in dynamic markets. This paper explores the synergy between innovation management theory and the capabilities of generative AI, offering a holistic perspective of its strategic challenges and opportunities to business leaders. Based on the concepts of dynamic capabilities theory, open innovation and recent empirical studies on the adoption of GenAI, we propose an integrated theoretical framework that conceptualizes GenAI as an enabler and disruptor of the existing innovation processes. Three specific areas of strategic challenges emerge from our analysis: organizational and cultural barriers, such as adaptation and resistance to change by the workforce; technical and governance issues, such as data quality and risk of AI hallucination; and ethical and regulatory issues, such as IP and algorithmic bias. At the same time, we pose three key strategic questions: how can innovation cycles be accelerated with automated ideation and prototyping? How can innovation be made accessible for everyone, by democratizing the process? And how can new business models emerge with content generated by AI? Finally, the paper offers practical managerial suggestions and a research agenda for scholars. The present work is a theoretically informed, but practically relevant, study at the intersection of artificial intelligence and strategic management, providing invaluable guidance for the innovation landscape in the era of GenAI.
Keywords: sap (socio-academic practitioner) programs on generative artificial intelligence, innovation management, dynamic capabilities, strategic leadership, digital transformation
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