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Submitted October 8, 2026
Published 2026-10-15

Artículos

Vol. 8 No. 1 (2026): Revista Colegiada de la Ciencia

Artificial intelligence as a business strategy for innovation and competitiveness in MSMES of the Canto del Llano district, Santiago de Veraguas


DOI https://doi.org/10.48204/j.colegiada.v8n1.a11459

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References
DOI: 10.48204/j.colegiada.v8n1.a11459

Published: 2026-10-15

How to Cite

Pérez Martínez , A. A., & Donoso Olave , W. A. (2026). Artificial intelligence as a business strategy for innovation and competitiveness in MSMES of the Canto del Llano district, Santiago de Veraguas. Revista Colegiada De Ciencia, 8(1), 32–44. https://doi.org/10.48204/j.colegiada.v8n1.a11459

Abstract

The objective of this study was to assess the extent to which artificial intelligence (AI) can serve as a business strategy aimed at promoting innovation and competitiveness among MSMEs in the Canto del Llano district. A quantitative approach was used, employing a non-experimental, cross-sectional design with a descriptive-correlational focus. The population consisted of 214 active formal businesses, of which 139 were included in the sample; non-probabilistic convenience sampling was employed. The instrument was a structured questionnaire using a Likert scale, validated by experts with a coefficient of 0.985 and a

 

 

 

Cronbach’s alpha of 0.985. Statistical analysis was performed using Microsoft Excel and SPSS 26.0. The

main results reveal that 61.1% of business owners admit to having limited knowledge of AI, and only 8.3% use it in their operations; however, more than 80% recognize its potential. Hypothesis testing showed that perceptions of the potential impact of AI are significantly higher than the neutral point on the scale (value = 3), with test values of t = 2.167 and p = 0.032. It is concluded that, although actual adoption is still in its early stages, there is a widespread positive perception toward the incorporation of AI, contingent upon the availability of training, technological resources, and institutional support. The findings provide the first set of systematized empirical evidence on AI adoption in MSMEs in this district, with implications for the design of business digitalization policies in the region.

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