AI IN VOCATIONAL AND TECHNICAL EDUCATION: REVOLUTIONIZING SKILL-BASED LEARNING

AI provides TVET students with specialized education through adaptive teaching which integrates automated administrative processes into Technical and Vocational Education and Training (TVET). Student engagement increases and learning memorization improves and workforce readiness improves through AI-powered learning tools that employ intelligent tutoring systems with virtual simulations supported by machine learning algorithms. The implementation of AI in TVET faces several challenges since it affects data privacy through algorithms while needing advanced systems and costs substantial funds and remains inaccessible to people who lack digital capabilities. Using Socio-Technical Systems Theory and Diffusion of Innovations Theory and Skill-Biased Technological Change the study investigates TVET Artificial Intelligence development prospects including its operational challenges and business opportunities. The study underlines two crucial elements: both the development of moral AI frameworks and the establishment of effective teacher education together with digital technology and financial support to create inclusive AI systems. AI holds transformative potential for skill-based education provided organizations achieve ethical standard alignment in their planning activities and guarantee universal access to its advantages. Research efforts should prioritize both long-term projects about AI policy development and the establishment of fair practices and clear system operations with accessible services. KEYWORDS: AI in TVET, Artificial Intelligence in Education, Adaptive Learning, Vocational Training, Ethical AI Frameworks, Digital Divide, Teacher Training, Workforce Readiness, Intelligent Tutoring Systems, Educational Technology Policy