V2I11P47

AI- Based Intelligent Career Counselor

Gaurang Punse^1*, Surabhi Chavhan¹, Arya Deshpande¹, Dev Dolas¹, Piyush Paunikar¹

Abstract

The integration of Artificial Intelligence (AI) into career guidance represents a transformative shift from traditional, often inaccessible counselling methods to personalized, scalable, and data-driven solutions. This project details the design, development, and evaluation of an “Intelligent Career Counselling System,” a mobile-first platform built using Flutter, Supabase, and OpenAI’s GPT model. The system addresses critical gaps in existing career guidance, such as limited personalization, outdated market data, and lack of actionable insights, by implementing a sophisticated adaptive assessment engine and an AI-powered recommendation engine. The adaptive assessment engine utilizes conditional branching across 20+ question types—covering personality, skills, interests, and learning preferences—to create a personalized evaluation experience, reducing average completion time to 12.8 minutes while maintaining a 96% completion rate. The AI engine generates specific, actionable recommendations, including target companies like TCS and Flipkart, relevant courses with INR pricing, professional certifications, and a structured 90-day action plan. A robust fallback system ensures 100% recommendation delivery. Comprehensive testing demonstrated a System Usability Scale (SUS) score of 82.4, a Net Promoter Score (NPS) of +56, and a user satisfaction rating of 4.3/5. The system achieved full WCAG 2.1 AA accessibility compliance and operated effectively under loads of up to 100 concurrent users. This research validates the efficacy of combining adaptive testing with AI to democratize high-quality career guidance, making it a viable, cost-effective solution for students and early-career professionals, particularly in the Indian context. The project establishes a foundation for future innovations in AI-enhanced educational technology.

Keywords:

Career Counselling, Artificial Intelligence, Adaptive Assessment, Flutter, OpenAI, Mobile Application, Personalized Learning