In the fast-paced field of information technology, continuous evaluation and improvement of professional competencies are crucial for maintaining competitiveness. This paper presents an innovative conceptual model designed to objectively assess the knowledge and skills of IT professionals, with a specific focus on UX/UI designers. The system incorporates advanced machine learning algorithms, such as Long Short-Term Memory (LSTM) networks, the Text-to-Text Transfer Transformer (T5) architecture, and the GPT-4 model, to automate the process of generating test questions and evaluating competency levels. Additionally, the concept system leverages fuzzy logic methods to enhance the assessment of qualitative and subjective competencies, particularly in UX/UI design tasks. By treating evaluation criteria as linguistic variables with corresponding membership functions, fuzzy logic enables the transition from qualitative to quantitative assessments. This approach allows for more flexible and precise evaluation of competencies, addressing the inherent uncertainty in creative and design-related tasks. A key feature of the system is the development of a competency matrix that includes design skills, research abilities, and soft skills, enabling a comprehensive assessment of a specialist’s qualifications. The study details the architecture of the assessment model. The methodology supports adaptive learning by continuously refining the competency evaluation process based on feedback from test results. Additionally, the system’s potential for integration into educational and professional development programs is examined, with promising implications across various IT sectors. The conceptual model as a whole improves the learning process and general professional development of IT professionals. Further research will focus on further improving the algorithms and expanding the application of the system to additional IT specializations.