Analyzing academic acceptance of artificial intelligence using extended technology acceptance model
Abstract
This study aims to analyze the acceptance of artificial intelligence (AI) technology among Indonesian academics using extended technology acceptance model (TAM). The analysis involved general extended technology acceptance model for e-learning (GETAMEL) independent variables, which include subjective norm (SN), experience (EXP), enjoyment (ENJOY), computer anxiety (CA), and self-efficacy (SE), as well as mediator variables: perceived usefulness (PU) and perceived ease of use (PEOU). This study uses technology innovations (TI) as moderator variable and behavioral intention (BI) as a dependent variable. The analysis reveals that SN has a significant influence over PU but not PEOU. ENJOY and SE have a significant positive influence over both PU and PEOU, while EXP and CA don’t have a significant influence over both variables. PU and PEOU have a significant positive influence over BI. TI strengthens the relation between PU and BI, but weakens the relation between PEOU and BI. This finding provides an important outlook for developing a strategy to increase the acceptance of AI technology in the academic environment through an approach that takes into account the factors of pleasure, self-confidence, and TI.
Keywords
AI technology acceptance; Artificial intelligence; Extended technology acceptance model; Higher education; PLS-SEM; Students’ acceptance; Technology innovativeness
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PDFDOI: http://doi.org/10.11591/ijai.v15.i4.pp3090-3102
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Copyright (c) 2026 Nanang Suryadi, Abdurrahman Hakim, Adelia Shabrina Prameka, Wildan Syafitri, Muhammad Irfan Islami

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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938
This journal is published by the Institute of Advanced Engineering and Science (IAES).