Generative AI Adoption and Productivity Outcomes in Small and Medium Enterprises
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Issued Date
2026-01-01
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Scopus ID
2-s2.0-105041283328
Journal Title
International Conference on Cybernetics and Innovations Icci 2026
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SCOPUS
Bibliographic Citation
International Conference on Cybernetics and Innovations Icci 2026 (2026)
Suggested Citation
Satayapaisal S., Ketcham M., Tantiathimongkhon T. Generative AI Adoption and Productivity Outcomes in Small and Medium Enterprises. International Conference on Cybernetics and Innovations Icci 2026 (2026). doi:10.1109/ICCI68752.2026.11506501 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/117333
Title
Generative AI Adoption and Productivity Outcomes in Small and Medium Enterprises
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Abstract
The rapid emergence of Generative AI (GenAI) tools such as ChatGPT, Google Gemini, and Canva AI has fundamentally transformed business operations, yet small and medium enterprises (SMEs) face unique challenges in selecting and integrating these technologies due to resource constraints. This study develops a strategic framework for GenAI adoption in SMEs by integrating Task-Technology Fit (TTF) and the Technology Acceptance Model (TAM) to evaluate how multi-modal AI capabilities influence organizational productivity and innovation. A quantitative survey was conducted with 150 SME owners, senior managers, and IT decision-makers who have integrated at least one GenAI tool into their business operations. Data were analyzed using descriptive statistics, One-Way ANOVA, Multiple Regression, and Pearson Correlation. The findings reveal that ChatGPT dominates adoption at 82%, followed by Canva AI (65.3%) and Google Gemini (48%). Multiple Regression analysis indicates that Perceived Ease of Use (β=0. 4 2, p<0. 0 0 1) and Data Accuracy (β=0. 3 5, p<0. 0 0 1) are the strongest predictors of business productivity, while Tool Versatility shows no significant effect. ANOVA results demonstrate significant differences in productivity gains across industry sectors (F= 5.84, p<0.01), with service-oriented SMEs deriving greater benefits from multi-modal capabilities compared to manufacturing sectors. These findings provide empirical evidence that successful GenAI integration requires strategic alignment between tool usability, output reliability, and industry-specific operational needs rather than merely adopting the most feature-rich platform.