Complementarity in Human-AI Collaboration : Concept, Sources, and Evidence

Title data

Hemmer, Patrick ; Schemmer, Max ; Kühl, Niklas ; Vössing, Michael ; Satzger, Gerhard:
Complementarity in Human-AI Collaboration : Concept, Sources, and Evidence.
In: European Journal of Information Systems. Vol. 34 (2025) Issue 6 . - pp. 979-1002.
ISSN 1476-9344
DOI: https://doi.org/10.1080/0960085X.2025.2475962

Official URL:

Abstract in another language

Artificial intelligence (AI) has the potential to significantly enhance human performance across various domains. Ideally, collaboration between humans and AI should result in complementary team performance (CTP)—a level of performance that neither of them can attain individually. So far, however, CTP has rarely been observed, suggesting an insufficient understanding of the principle and the application of complementarity. Therefore, we develop a general concept of complementarity and formalize its theoretical potential as well as the actual realized effect in decision-making situations. Moreover, we identify information and capability asymmetry as the two key sources of complementarity. Finally, we illustrate the impact of each source on complementarity potential and effect in two empirical studies. Our work provides researchers with a comprehensive theoretical foundation of human-AI complementarity in decision-making and demonstrates that leveraging these sources constitutes a viable pathway towards designing effective human-AI collaboration, i.e., the realization of CTP.

Further data

Item Type:	Article in a journal
Refereed:	Yes
Keywords:	Human-AI complementarity; human-AI decision-making; human-AI teams; human-AI collaboration; complementarity potential; complementarity effect
Institutions of the University:	Faculties Faculties > Faculty of Law, Business and Economics Faculties > Faculty of Law, Business and Economics > Department of Business Administration Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Informatics and Human-Centered Artificial Intelligence Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Informatics and Human-Centered Artificial Intelligence > Chair Business Informatics and Human-Centered Artificial Intelligence - Univ.-Prof. Dr.-Ing. Niklas Kühl Research Institutions Research Institutions > Central research institutes > Research Center for AI in Science and Society Research Institutions > Affiliated Institutes Research Institutions > Affiliated Institutes > Branch Business and Information Systems Engineering of Fraunhofer FIT Research Institutions > Affiliated Institutes > FIM Research Center for Information Management Research Institutions > Central research institutes
Result of work at the UBT:	Yes
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science 300 Social sciences > 330 Economics
Date Deposited:	01 Sep 2025 07:51
Last Modified:	01 Dec 2025 11:13
URI:	https://eref.uni-bayreuth.de/id/eprint/94554