Generative AI, Innovation, and Trust
Our paper explores the integration of generative artificial intelligence (GenAI) into organizations’ innovation and new product development processes, focusing on when and how to trust AI-generated outcomes in this context. We propose a framework to assess the level of trust required based on task-specific needs and the distinction between general and expert AI models. While inaccuracies in GenAI outputs can foster creativity during ideation, higher accuracy, and trust are essential for tasks requiring domain-specific expertise. The paper concludes by discussing the necessary human capabilities and organizational strategies for effectively deploying GenAI in innovation management.
Authors
- Frank Thomas Piller (ORCID: https://orcid.org/0000-0003-2532-4020)
- Tucker J. Marion (ORCID: https://orcid.org/0000-0002-1238-430X)
- Mahdi Srour
Institutions
- Northeastern University (US)
- RWTH Aachen University (DE)
Publication Details
- Journal
- The Journal of Applied Behavioral Science
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1177/00218863241285033
- Citations
- 20
- Primary Topic
- Innovation, Sustainability, Human-Machine Systems
- Type
- article
- Field-Weighted Citation Impact
- 22.64
Funders
- Deutsche Forschungsgemeinschaft
- Directorate for Engineering