DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE ADOPTION READINESS INDEX FOR SMALL INDUSTRIES IN WEST SUMATRA

Aisyah, Aisyah (2026) DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE ADOPTION READINESS INDEX FOR SMALL INDUSTRIES IN WEST SUMATRA. S1 thesis, Universitas Andalas.

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Abstract

Small industries have an important role in the economy of West Sumatra, but still face various challenges in increasing competitiveness, especially in adopting Artificial Intelligence (AI) technology. This study aims to analyze the influence of dynamic capabilities on AI adoption readiness in small industries and calculate the AI Adoption Readiness Index as a tool to assess the level of readiness. The research model focuses on three dimensions of dynamic capabilities, namely sensing, seizing, and transforming. AI adoption readiness is measured through four control variable domains, namely technology readiness, human resources, data management, and organizational readiness. This study uses a descriptive approach and quantitative explanation. Primary data was collected through surveys and questionnaires open to small industry respondents in West Sumatra. Secondary data is obtained from industry reports, national statistics, and relevant literature. The relationships between variables were analyzed using Structural Equation Modeling (SEM) with the Partial Least Squares (PLS) approach. The results showed that the model had a moderate explainability with an Rsquare value of 0.673, which means that 67.3 percent of the variation in AI adoption readiness can be explained by the variables in the model. The results of the hypothesis test showed that sensing (β = 0.458, p < 0.001) and transforming (β = 0.390, p = 0.006) capabilities had a positive and significant influence on AI adoption readiness. Meanwhile, seizing capabilities and control variables such as business age, number of employees, location, and subsectors did not show a significant influence. These findings underscore the importance of strengthening sensing and transforming capabilities to suppor

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