AI-Powered Skill Gap Identification and Career Guidance Platform Using Machine Learning and Natural Language Processing
Keywords:
Skill gap analysis, career guidance, machine learning, NLP, recommendation system, employability analytics.Abstract
The rapid transformation of industry driven by automation, artificial intelligence, and digital services has significantly altered workforce requirements. A major consequence of this transformation is the widening gap between the skills possessed by individuals and the competencies demanded by employers. Conventional career guidance mechanisms are typically static, manually driven, and poorly aligned with real-time labour market dynamics.
This paper presents an AI-powered skill gap identification and career guidance platform that integrates natural language processing, machine learning, and recommendation techniques to provide personalized career pathways. The proposed system automatically extracts skills from user profiles and resumes, predicts suitable job roles, computes a Skill Gap Index (SGI), and recommends targeted learning resources. The platform is implemented using a lightweight machine learning pipeline and a web-based service architecture. Experimental results demonstrate that the system can reliably identify user skills, predict relevant career roles, and generate actionable recommendations for upskilling. The proposed framework offers a scalable and transparent decision-support solution for modern career development ecosystems.
