Artificial intelligence (AI) has emerged as a transformative force across various sectors, including education and the workplace. This study explores the factors that influence the perception of AI as an innovation in academic work environments. Using a quantitative, cross-sectional design, data were collected from 325 individuals through a structured questionnaire and analyzed using a probit regression model. The findings reveal that the perception of AI as innovative is significantly associated with its perceived role in facilitating learning, its use in academic activities, agreement with the adaptation of educational models, and its ethical acceptability. Conversely, concerns about originality and heightened ethical responsibility appear to temper the perception of AI as a novel solution. The results emphasize that innovation is not only driven by technical use or frequency of exposure but also by pedagogical integration, institutional support, and ethical alignment. The study contributes to a deeper understanding of the sociotechnical factors shaping technology acceptance and provides recommendations for ethical and effective AI integration in educational settings.

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Factors Influencing the Perception of Artificial Intelligence as a Tool in the Workplace: A Probit Analysis from an Academic Context

  • María Eugenia Reyes-Pedraza,
  • Noé Emmanuel Del-Real-Garcia,
  • María Delia Tellez-Castilla

摘要

Artificial intelligence (AI) has emerged as a transformative force across various sectors, including education and the workplace. This study explores the factors that influence the perception of AI as an innovation in academic work environments. Using a quantitative, cross-sectional design, data were collected from 325 individuals through a structured questionnaire and analyzed using a probit regression model. The findings reveal that the perception of AI as innovative is significantly associated with its perceived role in facilitating learning, its use in academic activities, agreement with the adaptation of educational models, and its ethical acceptability. Conversely, concerns about originality and heightened ethical responsibility appear to temper the perception of AI as a novel solution. The results emphasize that innovation is not only driven by technical use or frequency of exposure but also by pedagogical integration, institutional support, and ethical alignment. The study contributes to a deeper understanding of the sociotechnical factors shaping technology acceptance and provides recommendations for ethical and effective AI integration in educational settings.