The Next-Gen Commerce Graduate: Thriving in an AI-Driven Economy-An Empirical Analysis of Student Perceptions and Curriculum Relevance
DOI:
https://doi.org/10.47392/IRJAEM.2026.0398Keywords:
Artificial Intelligence, Commerce Education, Curriculum Relevance, Graduate Employability, Non-Parametric Analysis, Student PerceptionsAbstract
The rapid integration of Artificial Intelligence (AI) into global business workflows has fundamentally reshaped employability expectations, requiring modern commerce graduates to possess both analytical and technological capabilities. This empirical study investigates commerce students' perceptions regarding AI adoption, their confidence in entering an AI-driven job market, and the perceived relevance of current higher education curricula. Primary data was gathered through a structured 5-point Likert scale questionnaire administered to N = 150 undergraduate (70%) and postgraduate (30%) commerce students across various specializations. Given the non-normal, ordinal nature of the data, descriptive statistics (Medians and Interquartile Ranges) and non-parametric inferential methods—including Spearman’s rank correlation, the Mann-Whitney U test, and the Kruskal-Wallis H test—were employed for hypothesis testing. The findings reveal that informal or active usage of AI tools does not significantly correlate with perceived career confidence (rs = .138, p = .091). Instead, graduate job market confidence depends strongly on formal institutional curriculum adequacy (rs = .665, p < .001). Comparative analysis showed significant differences in curriculum perception across academic levels (p = .005), with undergraduates expressing greater dissatisfaction than postgraduates. Furthermore, job confidence varied significantly across specializations (p < .001), with Business Analytics students reporting lower confidence (Mean Rank = 43.40) than traditional streams, reflecting heightened critical awareness of industry technical demands. The study concludes that higher education institutions must urgently reform commerce curricula by embedding applied AI applications, automated analytics, and algorithmic decision-making to bridge the gap between academic preparation and workforce expectations.
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