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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: April 2026
Volume 11 | Issue 4
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Impact Factor : 8.14
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| Paper Title: | AI-Powered Career Guidance System: An Intelligent Framework for Personalized Career Recommendation and Skill Pathway Generation |
| Authors Name: | Yuvraj Johare , Vaibhav Devkar , Sumit Chaudhari , Yashraj Garje |
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IJRTI_210187
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| Published Paper Id: | IJRTI2603029 |
| Published In: | Volume 11 Issue 3, March-2026 |
| DOI: | |
| Abstract: | The rapid expansion of academic specializations and career opportunities has made decision-making increasingly difficult for students and early professionals. Traditional career counselling methods—based on subjective analysis, limited psychometric tests, or one-time assessments—often fail to deliver personalized, data-driven, and objective recommendations. The need for an intelligent, scalable, and adaptive guidance system has therefore become essential in modern educational ecosystems. This paper presents an AI-Powered Career Guidance System that leverages machine learning, natural language processing (NLP), and large language models (LLMs) to provide end-toend personalized career recommendations. The system evaluates user skills, interests, and behavioral patterns through assessments, semantic analysis, and structured profiling. Based on these inputs, it generates suitable career-role mappings, learning pathways, project suggestions, and competency insights. Additional modules—such as resume generation and AI-driven mock interview evaluation—enhance employability preparation. Using deep learning models, transformer-based text understanding, and domain-skill similarity scoring, the system offers high contextual accuracy and adaptability. The proposed system aims to democratize career guidance by offering low-cost, real-time, and personalized recommendations accessible to all learners, regardless of geographical or economic constraints. Performance evaluation conducted on 60 students demonstrates 84.5% recommendation accuracy, 86% roadmap relevance, and a user satisfaction rating of 9/10, showcasing the potential of AI-driven systems in transforming educational and professional counselling. |
| Keywords: | Career Guidance, Artificial Intelligence, Machine Learning, Recommendation System, NLP, Deep Learning, LLM, Mock Interview. |
| Cite Article: | "AI-Powered Career Guidance System: An Intelligent Framework for Personalized Career Recommendation and Skill Pathway Generation", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 3, page no.a196-a202, March-2026, Available :http://www.ijrti.org/papers/IJRTI2603029.pdf |
| Downloads: | 000158 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2603029
Registration ID:210187
Published In: Volume 11 Issue 3, March-2026
DOI (Digital Object Identifier):
Page No: a196-a202 Country: pune, Maharashtra, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2603029 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2603029 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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