ARTIFICIAL INTELLIGENCE TO ENHANCE GRADUATES’ EMPLOYABILITY IN TECHNICAL AND VOCATIONAL EDUCATION AND TRAINING: A SYSTEMATIC LITERATURE REVIEW - Danyl Mallisza; Ikhwan Rahman (Journal of Scientech Research and Development, 2026)
The advancement of Artificial Intelligence (AI) has transformed competency requirements and workforce demands, necessitating adaptations in Technical and Vocational Education and Training (TVET) to enhance graduates' employability and career readiness. This Systematic Literature Review (SLR) aims to analyze AI's contribution to the development of graduate competencies and employability, while identifying the implications, opportunities, and challenges regarding career readiness within the TVET context. The study examined 12 articles sourced from Scopus and Google Scholar, systematically analyzing them based on research focus, findings, and contributions. The results indicate that AI supports the development of technical, digital, cognitive, and adaptive competencies relevant to industry needs, while also strengthening problem-solving skills, critical thinking, creativity, and work readiness. Conversely, while AI integration creates opportunities for more adaptive and career-oriented learning, it faces challenges related to curriculum readiness, educator competence, digital infrastructure, ethical considerations, and the digital access gap. These findings underscore the need to direct AI integration in TVET toward strengthening competencies relevant to job transformation and enhancing graduates' career readiness.