Contents I. INTRODUCTION
Career guidance is important in shaping students' futures, as it assists them with aligning their abilities, interests and aspirations with suitable opportunities. However, it is not that rural students do not access counseling; it is that they simply cannot afford it due to cost, language, and the outdated model of career counseling where the only variable considered is academic achievement. The constraints contribute to poor choices, skills gap, and lack of employability, elevating the urgency for better options. The non-academic measures of personality, behavior, and emotional intelligence, equally important for long-term career satisfaction, cannot be adequately captured using existing measures. New and promising approaches of artificial intelligence (AI) and machine learning (ML), will be able to address the limitations of traditional measures as they will be able to process multi-dimensional datasets incorporating academic, psychometric, and behavioral variables to provide personalized recommendations.
