The rapid increase in generative artificial intelligence (Gen AI) products has revolutionised the interaction between humans and artificial intelligence. However, the conceptualisation, measurement, and performance implications of human-AI interaction in the workplace remain underexplored. This study utilised a grounded theory approach to explore the multidimensional construct of human-AI interaction.
We then developed a measurement scale for human-AI interaction in the workplace using inductive and deductive methods. Finally, based on self-concept theory, we explored the mechanisms through which human-AI interaction is associated with task performance in the workplace. The results show that (1) human-AI interaction consists of three dimensions: anthropomorphic tool, adaptive trust, and unidirectional emotional connection. (2) The developed scale contained 19 items with good reliability and validity. (3) Human-AI interaction is positively associated with employees’ task performance, and role identity and self-efficacy partially mediate the relationship between human-AI interaction and task performance.
This research was funded by the National Natural Science Foundation of China (72402063, 72172065), Hubei Provincial Social Science Foundation Project (grant number HBSKJJ20233239), Hubei Provincial Department of Education Philosophy and Social Science Research (grant number 23Q112), and Hubei University of Technology High-level Talent Project (grant number XJ2022004701), Ministry of Education, Philosophy and Social Science Research Major Project(21JZD030), Wuhan Municipal Knowledge and Innovation Specialized Basic Research Project(2023010201010120). School of Economics and Management, Hubei University of Technology, Wuhan, China Hubei Digital Industrial Economy Development Research Center, Hubei University of Technology, Wuhan, China Business School, Nankai University, Tianjin, China School of Economics and Management, China University of Geosciences, Wuhan, China The authors declare no competing interests. The authors did not use any large language models (e.g., ChatGPT and Claude) to write or improve the language and readability of the manuscript during its preparation.
This study received ethical approval from the Institutional Review Board of Hubei University of Technology (approval no. 20240044) (see Related files). All procedures performed in this study adhered to the ethical standards outlined in the Declaration of Helsinki. The confidentiality and anonymity of the participants were strictly maintained to protect their privacy throughout the study.
This study employed surveys and interviews with employees who had experience using AI in workplace settings and did not involve any experiments. Informed consent was obtained from all participants before data collection. Participation was voluntary, and respondents were assured of anonymity, confidentiality, and the right to withdraw at any time.
All personal information and data collected were kept strictly confidential and were used solely for academic research. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material.
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