Generative AI, Innovation, and Trust

The Journal of Applied Behavioral Science, vol. 60, pp. 613–622

Abstract

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 3

1. Frank Thomas Piller corresponding Aachen School of Business and Economics

   RWTH Aachen University

   Affiliation as printed

   School of Business and Economics, RWTH Aachen University, Aachen, Germany

2. Mahdi Srour

   Northeastern University

   Affiliation as printed

   D’Amore-McKim School of Business, Entrepreneurship & Innovation Group, Northeastern University, Boston, MA, USA

3. Tucker James Marion

   Northeastern University

   Affiliation as printed

   D’Amore-McKim School of Business, Entrepreneurship & Innovation Group, Northeastern University, Boston, MA, USA