Augmenting human innovation teams with artificial intelligence: Exploring transformer-based language models
Sebastian G. Bouschery, Vera Blazevic, Frank T. Piller
kHUB post date: July 10, 2023
Originally published: January 10, 2023 (PDMA JPIM • Vol 40, Issue 2 • March 2023)
Read time: 40 minutes
Access the Full Article
The use of transformer-based language models in artificial intelligence (AI) has increased adoption in various industries and led to significant productivity advancements in business operations. This article explores how these models can be used to augment human innovation teams in the new product development process, allowing for larger problem and solution spaces to be explored and ultimately leading to higher innovation performance. The article proposes the use of the AI-augmented double diamond framework to structure the exploration of how these models can assist in new product development (NPD) tasks, such as text summarization, sentiment analysis, and idea generation. It also discusses the limitations of the technology and the potential impact of AI on established practices in NPD. The article establishes a research agenda for exploring the use of language models in this area and the role of humans in hybrid innovation teams. (Note: Following the idea of this article, GPT-3 alone generated this abstract. Only minor formatting edits were performed by humans.)
Practitioner points
- Transformer-based language models like GPT-3 are a powerful type of AI that can perform various tasks during an innovation process like text summarization, sentiment analysis, insight generation, or idea generation at an incredible scale.
- Such technologies support the exploration of larger problem and solution spaces and can augment humans to improve innovation performance.
- Artificial intelligence and humans will increasingly work together in a form of hybrid intelligence, which calls for a re-evaluation of how we approach and manage innovation.