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Operational AI Opportunity Formation in Small Industry: A TOE-DOI Explanation Ikhwan Arief; Prima Fithri; Angelina Ajeng Masayu; A Aisyah
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 2 (2026): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v7i2.10664

Abstract

Artificial intelligence (AI) is increasingly accessible to small firms, but prior studies mainly explain readiness, adoption, or downstream value rather than the stage at which AI first becomes visible as an operational opportunity. This study examines that upstream stage in small industrial firms by combining technology-organization-environment (TOE) antecedents with diffusion of innovation (DOI) outcomes. A purposive, census-oriented survey was conducted on the official West Sumatra small-industry frame. The final dataset contains 51 usable responses from 69 registered small industrial firms, equal to 73.91% official-frame coverage, and was analyzed with PLS-SEM in SmartPLS 4. A conservative rerun removed one weak infrastructure indicator while retaining the same inner model. The main supported path is human resources and digital literacy to observability (β = 0.609, p = 0.001, f² = 0.318), followed by governance, strategy, and budget support to observability (β = 0.447, p = 0.030, f² = 0.179). Observability reaches R² = 0.496, whereas infrastructure, data management, competitive pressure, and ecosystem support do not show comparable direct effects. The findings indicate that early AI opportunity becomes visible mainly through interpretive workforce capacity and bounded managerial support.