The Employability Paradox in the AI Era: How the ‘Efficacy Gap’ In Business Curricula Hinders Technological Readiness

Authors

Ivo Soares

CINAV, Escola Naval, Instituto Universitario Militar (Portugal)

Article Information

DOI: 10.47772/IJRISS.2026.10200105

Subject Category: Management

Volume/Issue: 10/2 | Page No: 1407-1419

Publication Timeline

Submitted: 2026-02-12

Accepted: 2026-02-17

Published: 2026-02-25

Abstract

Despite the Bologna Process’ emphasis on employability, concerns persist that higher education has not kept pace with the demands of Artificial Intelligence (AI)-intensive labour markets. This article examines the formal competence profile of Business Sciences curricula to explore this misalignment. Using quantitative content analysis, programme-level learning outcomes from 421 Business Sciences study cycles accredited by the Portuguese Agency for Assessment and Accreditation of Higher Education are analysed and mapped onto the USEM model through a validated competence matrix. The findings reveal a pronounced structural imbalance: while 85% of programmes explicitly include Knowledge-related outcomes (Understanding) and 63% include Technical-Scientific competences (Skills), only 35% refer to Efficacy-related transversal competences such as autonomous work, adaptation, continuous learning, or motivation for excellence. This configuration is conceptualised as an “Efficacy Gap” in the intended curriculum. Drawing on recent frameworks of AI Capital and Technological Readiness, the gap is interpreted as a structural condition that may constrain graduates’ capacity to convert disciplinary knowledge into adaptive, AI-enabled professional practice. The study contributes by (1) providing system-level evidence on the competence architecture of an entire national set of business programmes, (2) theoretically integrating the USEM model with emerging concepts of AI Capital and Technological Readiness, and (3) outlining implications for a transition from content-delivery towards readiness-oriented curricula that more explicitly foster autonomy, resilience, and lifelong learning as core conditions for employability in the AI era.

Keywords

The rapid integration of Artificial Intelligence (AI) into labour markets

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References

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