Artificial intelligence adoption future ready skills and graduate employability in higher education

Artificial intelligence (AI) is rapidly transforming higher education, making it essential to understand how students adopt and benefit from AI-enabled learning tools in ways that advance SDG 4. This study develops and validates a structural model examining how AI literacy, perceived usefulness, perceived ease of use and institutional support influence students’ adoption of AI applications, and how such adoption contributes to future-ready skills and graduate employability. Using a cross-sectional survey of 211 university students and analysing the data through PLS-SEM, the findings reveal that institutional support and perceived ease of use significantly predict AI adoption, whereas AI literacy has a significant negative effect and perceived usefulness has no significant effect on AI adoption. AI adoption strongly enhances future-ready skills, which subsequently exert a positive effect on graduate employability and mediate the relationship between AI adoption and employability outcomes. These results highlight the critical role of supportive institutional environments and intuitive AI design while indicating shifts in the factors shaping technology acceptance among learners. Overall, the study provides theoretical and practical insights for integrating AI responsibly and effectively in higher education to support SDG 4.

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Publication Details

Journal
Scientific Reports
Published
2026-07-28
DOI
https://doi.org/10.1038/s41598-026-64272-7
Primary Topic
Higher Education and Employability
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial intelligence adoption future ready skills and graduate employability in higher education

Saed Adnan Mustafa, Abdallah Altrad
Scientific Reports
Higher Education and Employability
article

Artificial intelligence adoption future ready skills and graduate employability in higher education

Saed Adnan Mustafa, Abdallah Altrad
article en

Abstract

Artificial intelligence (AI) is rapidly transforming higher education, making it essential to understand how students adopt and benefit from AI-enabled learning tools in ways that advance SDG 4. This study develops and validates a structural model examining how AI literacy, perceived usefulness, perceived ease of use and institutional support influence students’ adoption of AI applications, and how such adoption contributes to future-ready skills and graduate employability. Using a cross-sectional survey of 211 university students and analysing the data through PLS-SEM, the findings reveal that institutional support and perceived ease of use significantly predict AI adoption, whereas AI literacy has a significant negative effect and perceived usefulness has no significant effect on AI adoption. AI adoption strongly enhances future-ready skills, which subsequently exert a positive effect on graduate employability and mediate the relationship between AI adoption and employability outcomes. These results highlight the critical role of supportive institutional environments and intuitive AI design while indicating shifts in the factors shaping technology acceptance among learners. Overall, the study provides theoretical and practical insights for integrating AI responsibly and effectively in higher education to support SDG 4.

Scientific Reports
Applied Science Private University (JO), Cloud Computing Center (CN)
Openalex Percentile: Top 2%
Higher Education and Employability
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