AI-Powered Skill Gap Identifier And Career Guidance

Abstract

Rapid technological change is continuously reshaping job roles, skill requirements, and professional pathways. Traditional career guidance systems, which rely on static assessments and manual counseling, are no longer sufficient to support individuals in navigating complex and evolving labor markets. This paper presents the design, implementation, and evaluation of an Artificial Intelligence (AI)–driven Skill Gap Identifier and Career Guidance Platform (SGICGP).
The proposed system integrates machine learning, natural language processing, and labor-market intelligence to extract user skills from unstructured data, identify missing competencies, compute a Skill Gap Index (SGI), and generate personalized learning and career recommendations. A modular architecture is adopted to enable scalability, explainability, and continuous model updates. Experimental results obtained using a prototype implementation demonstrate reliable job-role prediction, accurate skill extraction, and actionable recommendations suitable for educational institutions and training providers.