TECHNOLOGICAL INNOVATION: ADOPTION OF ARTIFICIAL INTELLIGENCE IN MICRO, SMALL, AND MEDIUM ENTERPRISES (MSMES)
Abstract
This study examines the factors influencing the adoption of Artificial Intelligence (AI) technology among Micro, Small, and Medium Enterprises (MSMEs) in Indonesia. By integrating the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT), the research explores how perceived usefulness, perceived ease of use, and social influence impact MSME attitudes and behavioral intentions toward AI adoption. A quantitative method using path analysis and structural equation modeling (SEM) is employed to test the relationships between independent variables (AI adoption) and dependent variables (MSME performance), with data analysis conducted using Smart PLS 4.0 software. A quantitative approach is used to measure variables based on the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). This study explores the factors influencing the adoption and utilization of artificial intelligence (AI) in small and medium enterprises (SMEs) using a framework combining TAM and UTAUT. The findings highlight that perceived usefulness and effectiveness positively shape attitudes toward AI, as do ease of use and effort expectancy. Ease of use also enhances perceptions of AI’s usefulness and effectiveness. Behavioral intention to adopt AI is influenced by perceived benefits, ease of use, and social influence, with gender, age, and experience moderating these effects. Attitudes toward AI strongly drive behavioral intention, which subsequently leads to actual usage. Facilitating conditions, such as technological support and infrastructure, also play a key role in enabling usage, especially for experienced users and when adoption is voluntary. These findings emphasize the importance of usability, perceived value, and contextual factors in encouraging AI adoption in SMEs.
References
ACKNOWLEDGEMENT
This article is the output of a research grant for the regular Beginner Lecturer Research Program (PDP) scheme funded by the Directorate of Research, Technology and Community Service (DRTPM) with research grant contract number 112/E5/PG.02.00.PL/2024, 010/LL10/PG.AK/2024, 018.3/UAdz.1.2/Penelitian/2024. Thank you also to Adzkia University and those who have assisted in this research.
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