Track leaders:  

• Catherine Beaudry, Polytechnique Montréal, Canada 

• Davide Pulizzotto, Polytechnique Montréal, Canada 

• Vito Giordano, University of Pisa, Italy 

 

Innovation is a knowledge-intensive process, where much of the codified knowledge is stored in textual format embodied in, for instance, patents, research papers, and market reports. Natural Language Processing, a subfield of Artificial Intelligence, is a useful tool to support the management of innovation knowledge. The advent of Large Language Models (LLMs), like Google’s BERT and OpenAI’s GPT, has revolutionized the way we analyze and understand innovation phenomena and processes. LLMs offer immense potential for supporting firms in leveraging their knowledge assets by both analyzing existing knowledge and assisting in generating new knowledge. Their applications in the innovation process range from new product development processes to strategic innovation management. This track explores potential applications, novel methodologies, and challenges of employing LLMs to guide various stages of the innovation process. The track invites discussions on both the strategic and operational impacts of LLMs, highlighting their transformative role in fostering innovation.