Journal of Emerging Information Systems and Business Intelligence (JEISBI)
Vol. 7 No. 2 (2026): Vol. 07 Issue 02

Technology Readiness as a Higher-Order Driver of Perceived Ease and Usefulness of AI Tools

Imanuella Yesha Metanoia (Universitas Negeri Surabaya)
Ghea Sekar Palupi (Universitas Negeri Surabaya)



Article Info

Publish Date
28 Jul 2026

Abstract

Whether creative professionals embrace artificial intelligence (AI) depends not only on the tools themselves but on the psychological disposition users bring to technology. This study investigates technology readiness as a higher-order driver of the perceived ease of use and perceived usefulness that underpin AI adoption among Indonesian digital creatives. Grounded in the Technology Readiness and Acceptance Model (TRAM), technology readiness is modeled as a second-order reflective construct comprising two enabler dimensions, optimism and innovativeness, and two inhibitor dimensions, discomfort and insecurity, and is linked to perceived ease of use and perceived usefulness. Data from 355 practitioners were analyzed using partial least squares structural equation modeling (PLS-SEM) with the repeated-indicators approach and 5,000 bootstrap resamples. The higher-order construct was valid and reliable, and all four dimensions loaded significantly, with the reverse-coded inhibitor dimensions, insecurity and discomfort, carrying the highest loadings, followed by optimism and innovativeness. Technology readiness significantly and positively influenced both perceived ease of use and perceived usefulness, and perceived ease of use strongly influenced perceived usefulness. Perceived ease of use also partially mediated the effect of technology readiness on perceived usefulness. The findings show that overcoming discomfort and insecurity is as central to readiness as optimism and innovativeness, and that a favorable disposition makes AI tools feel both easier to use and, through that, more useful. The study contributes a dimension-level understanding of technology readiness and offers guidance for cultivating AI readiness in the creative industry.

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Journal Info

Abbrev

JEISBI

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Languange, Linguistic, Communication & Media Library & Information Science

Description

Journal of Emerging Information Systems and Business Intelligence (JEISBI) aims to provide scholarly literature focused on studies and research in the fields of Information Systems (IS) and Business Intelligence (BI). This journal also includes public reviews on the development of theories, methods, ...