Jakubik, JohannesVössing, MichaelKühl, NiklasWalk, JannisSatzger, Gerhard2024-10-302024-10-3020241867-0202http://dx.doi.org/10.1007/s12599-024-00857-8https://dl.gi.de/handle/20.500.12116/45343Data-centric artificial intelligence (data-centric AI) represents an emerging paradigm that emphasizes the importance of enhancing data systematically and at scale to  build effective and efficient AI-based systems. The novel paradigm complements recent model-centric AI, which focuses on improving the performance of AI-based systems based on changes in the model using a fixed set of data. The objective of this article is to introduce practitioners and researchers from the field of Business and Information Systems Engineering (BISE) to data-centric AI. The paper defines relevant terms, provides key characteristics to contrast the paradigm of data-centric AI with the model-centric one, and introduces a framework to illustrate the different dimensions of data-centric AI. In addition, an overview of available tools for data-centric AI is presented and this novel paradigm is differenciated from related concepts. Finally, the paper discusses the longer-term implications of data-centric AI for the BISE community.Data qualityData workData-centric artificial intelligenceText/Journal Article10.1007/s12599-024-00857-8