The contemporary job market is undergoing unprecedented transformation, driven by rapid technological advancements, globalization, automation, and the increasing demand for specialized skill sets. This dynamic landscape creates both opportunities and challenges for students, job seekers, and professionals, who often experience decision paralysis when navigating multiple career pathways. Traditional career guidance methods—such as standardized aptitude tests, manual counselling, or generic career portals—typically fail to deliver truly personalized recommendations, as they rarely consider the holistic profile of an individual. A career choice is not merely a function of academic achievements or professional experiences; it is also a synthesis of cognitive abilities, technical competencies, personality traits, and long-term aspirations. AI-powered career advisors bridge this gap by offering specialized guidance on these two important areas. The architecture has several sophisticated components and is built on a modular structure. First, we automatically parse resumes using Natural Language Processing (NLP) to extract structured information from unstructured language, including abilities, credentials, certificates, and work experiences. Then, in addition to rule-based methods using machine learning classifiers, it incorporates a hybrid MBTI classification module to assess some intrinsic personality factors that are essential to directing the individual toward job happiness and performance.
Agarkar et al. (Tue,) studied this question.