Paper Type
Complete
Paper Number
1838
Description
The rapid adoption of artificial intelligence (AI) technologies is transforming enterprises and challenging established paradigms, reshaping the landscape of business operations, strategy, and employee engagement. This technology shift is not without its complexities. Human-centric barriers, such as black-box issues and technology-related anxiety, can impede AI acceptance, hindering long-term success and integration of AI-based systems in organizational settings. This study posits that embracing AI decision support systems presents unique challenges, which are critical factors in end-user acceptance. We analyzed the literature and identified such factors, and conducted a survey of 218 respondents in a low-stake scenario with a modified Unified Theory of Acceptance and Use of Technology model. Our findings suggest that human-centric barriers necessitate reevaluating and expanding existing acceptance models, as well as generating explanatory knowledge for a more comprehensive understanding of AI acceptance and adoption.
Recommended Citation
Kučević, Emir; Leible, Stephan; Lewandowski, Tom; von Brackel-Schmidt, Constantin; and Ohlsen, Felix Paul, "A User-Based Study on the Acceptance of Artificial Intelligence-Based Decision-Support Systems" (2024). PACIS 2024 Proceedings. 3.
https://aisel.aisnet.org/pacis2024/track13_hcinteract/track13_hcinteract/3
A User-Based Study on the Acceptance of Artificial Intelligence-Based Decision-Support Systems
The rapid adoption of artificial intelligence (AI) technologies is transforming enterprises and challenging established paradigms, reshaping the landscape of business operations, strategy, and employee engagement. This technology shift is not without its complexities. Human-centric barriers, such as black-box issues and technology-related anxiety, can impede AI acceptance, hindering long-term success and integration of AI-based systems in organizational settings. This study posits that embracing AI decision support systems presents unique challenges, which are critical factors in end-user acceptance. We analyzed the literature and identified such factors, and conducted a survey of 218 respondents in a low-stake scenario with a modified Unified Theory of Acceptance and Use of Technology model. Our findings suggest that human-centric barriers necessitate reevaluating and expanding existing acceptance models, as well as generating explanatory knowledge for a more comprehensive understanding of AI acceptance and adoption.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.
Comments
Interaction