The Impact of Generative Artificial Intelligence on Ideation and the performance of Innovation Teams (Preprint)
Michael Gindert, Marvin Lutz M\"uller

TL;DR
This paper examines how Generative AI enhances innovation team performance by improving idea quality, diversity, and efficiency during the ideation phase, using a field experiment grounded in the Knowledge Spillover Theory.
Contribution
It introduces a novel AI-augmented ideation tool and empirically demonstrates GenAI's positive effects on innovation processes and team dynamics.
Findings
AI-augmented teams generated higher quality ideas
GenAI improved efficiency and knowledge exchange
Increased satisfaction and idea diversity among teams
Abstract
This study investigates the impact of Generative Artificial Intelligence (GenAI) on the dynamics and performance of innovation teams during the idea generation phase of the innovation process. Utilizing a custom AI-augmented ideation tool, the study applies the Knowledge Spillover Theory of Entrepreneurship to understand the effects of AI on knowledge spillover, generation and application. Through a framed field experiment with participants divided into experimental and control groups, findings indicate that AI-augmented teams generated higher quality ideas in less time. GenAI application led to improved efficiency, knowledge exchange, increased satisfaction and engagement as well as enhanced idea diversity. These results highlight the transformative role of the field of AI within the innovation management domain and shows that GenAI has a positive impact on important elements of the…
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Taxonomy
TopicsBig Data and Business Intelligence
