<![CDATA[The development of digital technology in the Industrial Revolution 4.0 era has driven transformation in various aspects of life, including in the field of education and counseling services. Increasingly complex global challenges demand an innovative approach in providing career guidance and social counseling services to students, especially at the Junior High School (SMP) level. One promising innovation is the application of deep learning technology, a branch of Artificial Intelligence (AI) that is able to process and analyze large amounts of data to produce personalized recommendations. This study uses a qualitative approach, descriptive research type. The method of collecting information through observation, in-depth interviews, and documentation. The research subjects include facilitator teachers, junior high school students, and principals. Through deep learning, the career guidance system can adapt to students' needs, potential, and interests more accurately, and detect social problems early on. This study aims to examine the potential for applying deep learning technology to improve the effectiveness of career guidance and social counseling services for junior high school students, as well as the challenges that may be faced in its implementation, especially related to infrastructure policies and education budgets. The constructivist approach is the basis for system design, which emphasizes active interaction between students and the environment as the key to the success of meaningful learning. The results of the study indicate that the integration of deep learning technologies in tutoring services can be an innovative solution to support students' career readiness and social and emotional well-being, although it requires infrastructure readiness, educator training, and educational policy support that supports digital transformation.]]>
