Harnessing Artificial Intelligence for Vocational Guidance: Opportunities, Challenges, and Implications for Technical and Vocational Education and Training (TVET) in Nigeria

Authors

Abdullahi Rabiu

Department of Technical Education, Northwest University Kano, Kano State (Nigeria)

Yusuf Musa Kibiya

Department of Educational Foundations, Northwest University Kano, Kano State (Nigeria)

Article Information

DOI: 10.47772/IJRISS.2026.10200294

Subject Category: Education

Volume/Issue: 10/2 | Page No: 4018-4034

Publication Timeline

Submitted: 2026-02-14

Accepted: 2026-02-23

Published: 2026-03-07

Abstract

The rapid advancement of Artificial Intelligence (AI) is reshaping educational systems and workforce development practices, with significant implications for vocational guidance within Technical and Vocational Education and Training (TVET). This study adopts a systematic conceptual review methodology to synthesise existing theoretical, empirical, and policy-oriented literature on the application of AI in vocational guidance. Drawing on Human Capital Theory and Social Cognitive Career Theory, the review examines how AI-enabled tools support personalised guidance, labour market alignment, and scalable career support services. The findings indicate that AI technologies such as labour market analytics, recommender systems, and intelligent virtual assistants offer substantial opportunities to enhance guidance effectiveness, improve employability outcomes, and strengthen school-to-work transitions. However, the review also identifies critical challenges, including ethical concerns, algorithmic bias, limited explainability, loss of human-cantered counselling, and persistent digital divide constraints, particularly in developing countries contexts. The study argues that AI should function as an augmentative tool that complements, rather than replaces, professional guidance Counsellors. By synthesising key themes and identifying gaps in current research, this article contributes a conceptual framework to inform policy development, institutional practice, and future empirical research on AI-enabled vocational guidance in TVET systems.

Keywords

Vocational guidance, AI-enabled career guidance, TVET systems, Labour market analytics

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