Fabri, LukasHäckel, BjörnOberländer, Anna MariaRieg, MariusStohr, Alexander2023-12-122023-12-1220231867-0202http://dx.doi.org/10.1007/s12599-023-00810-1https://dl.gi.de/handle/20.500.12116/43296Artificial intelligence (AI) offers great potential in organizations. The path to achieving this potential will involve human-AI interworking, as has been confirmed by numerous studies. However, it remains to be explored which direction this interworking of human agents and AI-enabled systems ought to take. To date, research still lacks a holistic understanding of the entangled interworking that characterizes human-AI hybrids, so-called because they form when human agents and AI-enabled systems closely collaborate. To enhance such understanding, this paper presents a taxonomy of human-AI hybrids, developed by reviewing the current literature as well as a sample of 101 human-AI hybrids. Leveraging weak sociomateriality as justificatory knowledge, this study provides a deeper understanding of the entanglement between human agents and AI-enabled systems. Furthermore, a cluster analysis is performed to derive archetypes of human-AI hybrids, identifying ideal–typical occurrences of human-AI hybrids in practice. While the taxonomy creates a solid foundation for the understanding and analysis of human-AI hybrids, the archetypes illustrate the range of roles that AI-enabled systems can play in those interworking scenarios.Archetypes||Human-AI collaboration||Human-AI hybrids||Sociomateriality||TaxonomyText/Journal Article10.1007/s12599-023-00810-1