CC BY-NC-ND 4.0Geurts, AmberAmberGeurtsGutknecht, RalphRalphGutknechtWarnke, PhilinePhilineWarnkeGoetheer, ArjenArjenGoetheerSchirrmeister, ElnaElnaSchirrmeisterBakker, BabetteBabetteBakkerMeissner, SvetlanaSvetlanaMeissner2022-03-0630.7.20212022https://publica.fraunhofer.de/handle/publica/26833410.24406/publica-r-26833410.1002/ffo2.99This paper outlines new perspectives for data-supported foresight by combining participatory expert-based futures dialogues with the power of artificial intelligence (AI) in what we call the hybrid AI-expert-based foresight approach. To this end, we present a framework of five typical steps in a fully fledged foresight process ranging from scoping to strategizing and show how AI can be integrated into each of the steps to enable the hybrid AI-expert foresight approach. Building on this, we present experiences gained from two recent research projects of TNO and Fraunhofer ISI that deal with aspects of the hybrid AI-expert foresight approach and give insights into the opportunities and challenges of the new perspectives for data-supported foresight that this approach enables. Finally, we summarize open questions and challenges for future research.enAIdata supported foresightframeworkhybrid AI‐expert‐based approachinnovation managementstrategic decision makingstrategic foresighttechnology managementtrend detection303600journal article