Paper Type
ERF
Abstract
This paper introduces the concept of Augmented Innovation, a paradigm that integrates Generative Artificial Intelligence (GenAI) with human creativity to enhance open innovation processes. Drawing on challenges inherent in traditional open innovation, such as strategic misalignment, process inefficiencies, and community fragmentation, the study explores how GenAI can augment decision-making, ideation, collaboration, and trust. Anchored in prior research on open innovation affordances, the paper presents a conceptual framework that delineates the strategic, procedural, and community-level contributions of GenAI. It also outlines a future research agenda emphasizing ethical considerations, contextual adaptability, and the need for interpretive case studies to ground theorization. This work advances a theoretical foundation for responsibly navigating the transition from open to augmented innovation.
Paper Number
2280
Recommended Citation
Abhari, Kaveh; Safaei Pour, Morteza; and Sanatizadeh, Aida, "Toward a Theory of Augmented Innovation: Navigating the Nuances and Trade-offs in Open Innovation" (2025). AMCIS 2025 Proceedings. 18.
https://aisel.aisnet.org/amcis2025/sig_dite/sig_dite/18
Toward a Theory of Augmented Innovation: Navigating the Nuances and Trade-offs in Open Innovation
This paper introduces the concept of Augmented Innovation, a paradigm that integrates Generative Artificial Intelligence (GenAI) with human creativity to enhance open innovation processes. Drawing on challenges inherent in traditional open innovation, such as strategic misalignment, process inefficiencies, and community fragmentation, the study explores how GenAI can augment decision-making, ideation, collaboration, and trust. Anchored in prior research on open innovation affordances, the paper presents a conceptual framework that delineates the strategic, procedural, and community-level contributions of GenAI. It also outlines a future research agenda emphasizing ethical considerations, contextual adaptability, and the need for interpretive case studies to ground theorization. This work advances a theoretical foundation for responsibly navigating the transition from open to augmented innovation.
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