Outlet Title

Proceedings of the 56th Hawaii International Conference on System Sciences

Document Type

Article

Publication Date

2023

Abstract

Artificial Intelligence (AI) technologies such as machine learning (ML), natural language processing (NLP), and image recognition, are being incorporated into a wide variety of applications. These AI-enabled applications (AI apps) promise to reshape people's lives. However, despite the proliferation of AI-related research, very little research has focused on how AI apps' unique characteristics affect an individual's adoption behavior. This study examines factors influencing an individual's intention to use AI apps with a proposed research model based on the Task Technology Fit (TTF) as the underlying theoretical framework. The research model is empirically evaluated using the survey data and SEM method. Theoretically, this study focuses on how the unique characteristics of AI apps influence the task-technology fit and drive the intention of use. The findings are expected to help AI app developers to evaluate the relative importance of AI app features which can provide insights into the technology characteristics and identify priorities for further research and development.

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