Paper Details

Name: Ishanika, Aman Agrawal, Katyayani, Aadyant Tripathi, Seema Kharod & Kirti Pandey
Country: India

Year: 2026
Volume: Volume No: 13, January, Year: 2026 (Special Issue)
Page Number: 888-894
DOI: https://doi.org/10.5281/zenodo.19144191

ABSTRACT—
With the speed at which Artificial Intelligence (AI) is advancing, new opportunities for personalized services have been opened up, including career counselling, to name but one. The paper describes the development of an AI-powered webbased AI-powered web-based Career Counselling and Recommendation System for users to make informed career choices. The goal is to offer real-time, personal career help using AI-driven predictions based on user data, i.e., skills, interests, and education. The proposed system allows web-facilitated user interaction and data entry, accessible from any device and browser. The backbone is Machine learning models that analyse user inputs, count career suitability, and recommend suitable careers. User-friendliness is the system's highest priority, providing ease of use with simple navigation and immediate feedback while keeping the system highly scalable and reliable. This work aims to fill the gap between conventional career counselling approaches and the rising betterment of virtualized, data-driven information. Integrating AI into the career decision-making framework allows the system to be applied to different user profiles and provide dynamic, evidence-informed responses. Moreover, because the platform is accessible to people of different backgrounds, it suits people from particular backgrounds. This research aims to share functional, underexplored transformative realms of AI that
can be applied to help crisis factors faced with career counselling and a roadmap for future development.

Keywords — AI-Powered Career Counselling, Web-Based Recommendation System, Personalized Career Advice, Machine Learning Models, Real-Time Career Recommendations.