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Analyzing academic acceptance of artificial intelligence using extended technology acceptance model

Research output: Contribution to journal › Article › peer-review

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.

Original languageEnglish
Pages (from-to)3090-3102
Number of pages13
JournalIAES International Journal of Artificial Intelligence
Volume15
Issue number4
DOIs
Publication statusPublished - Aug 2026

Keywords

  • AI technology acceptance
  • Artificial intelligence
  • Extended technology acceptance model
  • Higher education
  • PLS-SEM
  • Students' acceptance
  • Technology innovativeness

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