Innovating by prompting: How to facilitate innovation in the age of generative AI

Abstract

This article focuses on how recent advances in artificial intelligence (AI), particularly chatbots based on large language models (LLMs), such as ChatGPT, can be used for innovation purposes. The article begins with a brief overview of the development and characteristics of generative AI (GenAI). Elaborating on the implications of GenAI, we provide examples to demonstrate four mechanisms of LLMs: translation, summarization, classification, and amplification. These mechanisms inform a framework that highlights how LLMs enable the creation of innovative solutions for organizations through capacities in two dimensions: context awareness and content awareness. The strength of LLMs lies in the combination of capacities in both these dimensions, which enables them to comprehend and amplify content. Four managerial suggestions are presented, ranging from starting out with small-scale projects and data exploration, to scaling through integration efforts and educating prompt engineers. By presenting the framework, recommendations, and examples of use cases in various contexts, the article contributes to the emerging literature on GenAI and innovation.