What question did this study set out to answer?

The study aims to compare perceptions of AI's impact on employment among Romanian students and faculty, focusing on readiness and anxiety.

March 21, 2026Open Access

Replacement vs. Augmentation: An Analysis of Romanian Students and Faculty Views of the Impact of AI on the Labor Market

KAKamer-Ainur Aivaz DTDaniel TeodorescuClark Atlanta University OROana Roxana RaduOvidius University

Key Points

The study aims to compare perceptions of AI's impact on employment among Romanian students and faculty, focusing on readiness and anxiety.
Questionnaire administered to 271 respondents (197 students, 74 faculty)
Utilized descriptive and inferential statistics for data analysis
Employed Chi-square tests and binary logistic regression
Grounded in Unified Theory of Acceptance and Use of Technology (UTAUT) and Social Cognitive Theory (SCT)
Students express greater concern over job replacement compared to faculty
Both groups agree on AI's role in transforming labor
Personal and organizational readiness are key predictors of positive attitudes toward AI
Demographic factors lose significance when controlling for readiness variables

Abstract

The rapid development of artificial intelligence (AI) has intensified debates regarding its impact on the labor market, specifically concerning the potential for replacement versus the augmentation of human labor. While the existing literature highlights both the opportunities and risks associated with AI, research conducted by faculty in academic settings focuses predominantly on academic integrity, paying limited attention to AI readiness and/or anxiety related to labor market entry. This study aims to compare the perceptions of students and faculty in Romania regarding the impact of AI on employment, exploring the role of personal and organizational readiness in shaping these attitudes. The research is based on an empirical approach utilizing a questionnaire applied to a sample of 271 respondents, consisting of 197 students and 74 faculty members. Data analysis included descriptive and inferential methods, such as Chi-square tests and binary logistic regression, and was theoretically grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT) and Social Cognitive Theory (SCT). The results indicate significant differences between students and faculty regarding general attitudes toward AI, with students manifesting higher levels of concern regarding job replacement. However, both groups converge in their functional definition of AI as a major factor in labor transformation, suggesting an evaluative rather than a cognitive difference. Multivariate analyses show that personal readiness and the perception of organizational readiness are the primary predictors of a positive attitude toward AI, while demographic variables lose statistical significance when these dimensions are controlled. This study contributes to the literature by highlighting that AI-related anxiety is not inherently determined by demographic characteristics but represents a malleable state shaped by individual competencies and institutional conditions. The findings underscore the strategic role of universities in reducing perceptions of replacement and facilitating the transition to an AI-augmented labor market through training policies, adequate infrastructure, and transparent institutional communication.

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