Artificial Intelligence and Entrepreneurial Intention Among University Students in Honduras
Artificial Intelligence (AI) is transforming entrepreneurial ecosystems by enabling automation, data-driven decision-making, and innovative business models. The objective of this study was to analyze how university students from Universidad Tecnológica Centroamericana (UNITEC) perceive Artificial Intelligence and how their knowledge, attitudes, and technological skills influence their intention to apply AI in entrepreneurial initiatives. A quantitative, cross-sectional study was conducted using a structured questionnaire based on a five-point Likert scale. A total of 104 undergraduate students from the Faculty of Administrative and Social Sciences participated in the survey. The results show that 75% of students have general knowledge of Artificial Intelligence, 80% show positive attitudes toward its use in entrepreneurship, and 78% express intention to apply AI in future business initiatives. However, the findings also reveal a gap between students’ basic familiarity with AI tools and the level of advanced technical skills required for entrepreneurial application. The study concludes that while students demonstrate strong interest in AI-driven entrepreneurship, universities should strengthen practical training and technological education to help future entrepreneurs effectively integrate Artificial Intelligence into innovative business models.
Authors
- Hillary Nicole Chinchilla Chacón (ORCID: https://orcid.org/0009-0001-0952-448X)
- Laura Iris Castro Paz (ORCID: https://orcid.org/0009-0000-2529-0575)
- Andrea Camilla Zelaya Pineda (ORCID: https://orcid.org/0009-0004-3459-8052)
Institutions
- Central American Technological University (HN)
- Universidad de Tecnología y Comercio (NI)
- Center Technological University (VE)
- Technological University of Mexico (MX)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-05-12
- DOI
- https://doi.org/10.5281/zenodo.20148250
- Primary Topic
- E-Learning and Knowledge Management
- Type
- preprint