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@article{201821,
        author = {Sarmisstha S.K and Mrs.J.Mullai and Ranjani.T and Preetha.N},
        title = {AI-POWERED AGENTIC LEARNING AND WORKFORCE RELEVANCE PLATFORM PROTOTYPE},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {4813-4821},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201821},
        abstract = {The proposed system presents an AI-powered adaptive learning platform developed to provide personalized and career-oriented learning support for users. The platform analyzes user skills, educational background, and career goals to identify missing competencies and learning requirements. Based on the analysis, the system generates customized learning pathways and recommends suitable courses, certifications, and technical resources. An adaptive learning agent continuously monitors user progress and suggests the next appropriate skill to maintain continuous learning and improve engagement. The platform combines recommendation techniques, skill gap analysis, and progress tracking to support structured and efficient learning experiences. The developed framework helps users avoid unnecessary learning content while improving workforce readiness and technical skill development. Experimental results show that the system provides effective personalized guidance and serves as a reliable solution for intelligent learning and career growth.},
        keywords = {Adaptive Learning, Personalized Education, Skill Gap Analysis, Recommendation System, Workforce Relevance, Career Development, Intelligent Learning},
        month = {May},
        }