Abstract: Artificial Intelligence (AI) has increasingly been integrated into educational technologies, with particular attention to career guidance systems. This paper presents a comprehensive synthesis of six- teen existing research studies focused on AI-based career counselling and advisory platforms. Through detailed analysis, it was found that current approaches predominantly rely on classical machine learning models such as Decision Trees, Support Vector Machines, and Naive Bayes, alongside rule-based expert systems. A small subset of studies explored the use of neural networks, such as GRUs and attention mechanisms, yet deep learning remains underutilized.[1] Moreover, significant gaps were identified: lack of personalization, limited use of psychological profiling (example MBTI or RIASEC), insufficient integration with real-time labor market data, and poor accessibility in multilingual or mobile-first con- texts—especially in the Global South. Most systems are static, institution-specific, and rely on small datasets, limiting scalability and adaptability. Educational counseling is a pedagogical and social service that involves orienting students to find the most relevant academic or professional institutions according to their educational background and preferences. Its primary goal is to help students join the right path that aligns with their skills, where they can develop themselves and realize their full potential. It caters to students at all school levels, spanning from primary to higher education. Building on these findings, this research proposes a novel AI-powered career guidance framework that leverages deep learning, user modelling, and personality traits to deliver personalized, adaptive, and culturally contextual recommendations. This system aims to bridge the gap between education and employability by incorporating psychological, academic, and future-skill analytics into a unified, intelligent decision support platform.[6]

Keywords: keywords; Artificial Intelligence, Career Guidance, Deep Learning, Machine Learning, Psychometrics, Recommender Systems, BERT, NLP, User Modelling, MBTI, RIASEC, Labor Market Analytics, Adaptive Learning, Personalization, Decision Support Systems.

Downloads: | DOI: 10.17148/IARJSET.2025.12914