Designing an AI-Driven Career Guidance Framework in South African Higher Education: A User-Centric Approach

Abstract

The integration of Artificial Intelligence (AI) into career guidance systems presents a valuable opportunity to address the structural, informational, and psychological barriers that hinder effective decision-making for university students. This study outlines the development and implementation of a user-centred, AI-driven career guidance framework tailored for South African higher education institutions. Grounded in behavioural theory, particularly Social Cognitive Career Theory (SCCT), the framework was crafted using a qualitative research approach that incorporated insights from students’ focus group discussions and semi-structured interviews with lecturers. Findings show that students value personalised, context-sensitive guidance features, particularly those that link academic achievements to job market trends. Educators emphasised the need for system transparency, data security, and fair access to build trust and promote adoption. Results indicate AI-powered tools can boost students' confidence and career self-efficacy when integrated into academic support frameworks. The study highlights key contextual factors influencing career decision-making, such as the availability of reliable information, self-efficacy, the perceived usefulness of AI tools, and the digital readiness of institutions. The framework integrates machine learning profiling, personalised recommendations, and feedback loops, addresses inequalities, aligns education with labour-market needs, and helps students make career decisions. The evaluation findings show that stakeholders essentially embrace AI-powered guidance tools, though ongoing concerns include data privacy, confidence in the recommendations, and ensuring equal access. This paper offers a practical and theoretically informed model for career development interventions in developing contexts, serving as a blueprint for inclusive, scalable, and adaptable AI solutions in higher education.

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