Use Cases for AI in Technology Foresight: A Systematic Literature Review

Artificial Intelligence (AI) is undoubtedly a hype topic that has attracted considerable attention in the recent past. The rapid development and the promise that AI brings with it emphasizes its importance. However, it is crucial to note that AI is currently still no general-purpose problem solver. For AI to work, usable and comprehensive contextual data is required. In the field of technology foresight, there are several potential data sources. These include scientific publications, patents, and social media data such as X. These data sources enable Technology Foresight (TF) to make statements about the innovation system and to make a well-founded assessment of technological progress through identifying patterns. The aim is to increase the efficiency and effectiveness of TF. This article deals with the development of TF approaches through to the use of artificial intelligence. Therefore, we conducted a systematic literature review (SLR) on the topics of AI, data-driven approaches, and TF. The analysis of 221 relevant papers revealed 12 unique use cases for AI in TF. These use cases were classified based on selected characteristics, thereby providing a more comprehensive understanding of the application of these approaches in the context of TF.