Paper Title
Beyond Traditional Counseling: AI and ML in Career Guidance

Abstract
Artificial Intelligence (AI) and Machine Learning (ML) have greatly impacted career guidance through the provision of data-driven, personalized advice. Conventional methods of career recommendation are challenged in handling extensive numbers of diverse careers, which can result in poor decision-making. This paper performs an extended review of existing literature on career counseling systems utilizing AI, assessing different methodologies, datasets, and ML models to improve career and course guidance recommendations. The paper summarizes significant advances, challenges, and knowledge gaps of existing career recommendation systems. With these as premises, the paper presents an enhanced predictive model that incorporates user profiling, skill evaluation, and real time market trends to make more accurate and dynamic career recommendations. The outlined framework is set to increase alignment with abilities, personality assuring its relevance in the current scenario, ultimately maximizing career pathway planning. Keywords - Artificial Intelligence, Machine Learning, Career Counseling, Predictive Analysis, Personalized Recommendations, Educational Guidance, Recommender Systems, Career Decision-Making.