CAREER COMPASS: AN AI-SUPPORTED FRAMEWORK FOR CONTINUOUS INTERPERSONAL COMPETENCY DEVELOPMENT
Milen Todorov
Pages: 1-8
ABSTRACT: The increasing integration of artificial intelligence into education and career development creates new opportunities to move beyond static competency assessment toward continuous, personalized learning. Building upon the previously proposed System of Career Success in the Digital Age, this paper presents Career Compass an AI-based framework that operationalizes the conceptual model into a structured process for developing interpersonal career competencies. Rather than treating assessment as a one-time measurement, the proposed system transforms it into an iterative developmental journey supported by artificial intelligence.
The framework focuses on four core competencies - Empathy, Collaboration, Networking, and Leadership and guides users through a continuous development cycle consisting of motivation, self-assessment, AI-driven competency analysis, personalized goal setting, competency-focused coaching, micro-learning tasks, structured reflection, automated progress estimation, and periodic reassessment. The AI component functions not merely as a conversational assistant but as an adaptive career coach that interprets assessment data, generates personalized recommendations, facilitates behavioral reflection, and supports competency growth over time.
The proposed process introduces the concept of a Growth Journey Layer, which connects competency assessment with continuous AI-supported development. This layer enables dynamic adaptation of learning activities according to the user's evolving competency profile while preserving a complete history of progress. Consequently, the platform shifts the role of AI from an information provider toward an active facilitator of measurable professional development.
The contribution of this paper is threefold: (1) it operationalizes the conceptual System of Career Success into an AI- supported methodological framework and technological process; (2) it introduces a structured methodology for continuous competency development through iterative coaching and reflection; and (3) it proposes an architecture suitable for implementation in higher education and organizational learning environments. Future empirical studies will evaluate the effectiveness of the framework in supporting long-term competency growth.
Keywords: career development, artificial intelligence, interpersonal competencies, career coaching, competency assessment, higher education, agentic AI, lifelong learning
