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The research examines gender-related differences in educational institutions’ utilization and AI's effect on Digital Readiness (DR), Women's Engagement in Technology (WET), and Innovation Participation (INP). A validated survey was distributed through Google Forms to students and working professionals before we employed Structural Equation Modeling (SEM) with PLS to analyze direct effects and indirect effects, as well as multi-group analysis (MGA). The study establishes Perceived Ease of Use (PEU_AI) as a significant determinant linking to WET and INP through Digital Readiness (β = 0.336, p = 0.002 and β = 0.306, p = 0.007, respectively). The mediation paths measured through SEM demonstrate significance only for male respondents, while female respondents display weak or non-significant relationships between AI_HE and DR and INP variables (β = -0.003; p = 0.485). The research points out that systemic structure and cognitive challenges prevent women from taking advantage of artificial intelligence educational transformations and innovation solutions. .

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Empowering Women in Technology, Innovation, and Entrepreneurship in the AI Era: The Impact of Artificial Intelligence on Job Training

  • 章节

  • 发表日期：

    2026年

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  • Boumedyen Shannaq,
  • Said Alrawahi,
  • Saad Almhlawi

摘要

The research examines gender-related differences in educational institutions’ utilization and AI's effect on Digital Readiness (DR), Women's Engagement in Technology (WET), and Innovation Participation (INP). A validated survey was distributed through Google Forms to students and working professionals before we employed Structural Equation Modeling (SEM) with PLS to analyze direct effects and indirect effects, as well as multi-group analysis (MGA). The study establishes Perceived Ease of Use (PEU_AI) as a significant determinant linking to WET and INP through Digital Readiness (β = 0.336, p = 0.002 and β = 0.306, p = 0.007, respectively). The mediation paths measured through SEM demonstrate significance only for male respondents, while female respondents display weak or non-significant relationships between AI_HE and DR and INP variables (β = -0.003; p = 0.485). The research points out that systemic structure and cognitive challenges prevent women from taking advantage of artificial intelligence educational transformations and innovation solutions. .