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Paper Number
1644
Paper Type
Complete
Abstract
The increasing adoption of artificial intelligence (AI) in organizations has led to the emergence of human-AI hybrids, where human and AI agents collaborate on joint tasks. This paper presents a multiple case study exploring the challenges and good practices of constructing and executing such hybrid systems. Using a work system theory perspective, we identify nine challenges and nine good practices from four successfully implemented real world cases of human-AI hybrids, structured along the work system lifecycle. In line with our socio-technical approach, we identify two major stakeholder roles involved in the construction and execution of human-AI hybrids, the technical implementer and the organizational implementer, each of which faces unique challenges and applies different good practices. This research contributes to the growing body of knowledge on the implementation of human-AI hybrids in organizations and provides practical insights for managers and implementers seeking to successfully integrate AI into their work systems.
Recommended Citation
Mayer, Valentin; Schüll, Moritz; Aktürk, Onur; and Guggenberger, Tobias, "Designing Human-AI Hybrids: Challenges and Good Practices from a Multiple Case Study" (2024). ICIS 2024 Proceedings. 3.
https://aisel.aisnet.org/icis2024/aiinbus/aiinbus/3
Designing Human-AI Hybrids: Challenges and Good Practices from a Multiple Case Study
The increasing adoption of artificial intelligence (AI) in organizations has led to the emergence of human-AI hybrids, where human and AI agents collaborate on joint tasks. This paper presents a multiple case study exploring the challenges and good practices of constructing and executing such hybrid systems. Using a work system theory perspective, we identify nine challenges and nine good practices from four successfully implemented real world cases of human-AI hybrids, structured along the work system lifecycle. In line with our socio-technical approach, we identify two major stakeholder roles involved in the construction and execution of human-AI hybrids, the technical implementer and the organizational implementer, each of which faces unique challenges and applies different good practices. This research contributes to the growing body of knowledge on the implementation of human-AI hybrids in organizations and provides practical insights for managers and implementers seeking to successfully integrate AI into their work systems.
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