<![CDATA[This study aims to examine the level of competence of prospective mathematics teachers in integrating Artificial Intelligence within the Technological Pedagogical and Content Knowledge framework. The research focuses on analysing several knowledge domains, including Pedagogical Knowledge, AI-Technological Content Knowledge, AI-Technological Pedagogical Knowledge, and AI-Technological Pedagogical and Content Knowledge. A quantitative descriptive method was employed using a survey distributed to 110 prospective mathematics teacher students selected through purposive sampling . The collected data were analysed using descriptive statistics based on percentages to determine participants’ competency levels across the measured indicators. The findings reveal that most participants demonstrate adequate competence in pedagogical knowledge, particularly in selecting appropriate teaching methods, adapting instruction based on student feedback, and considering students’ backgrounds and learning needs. In terms of AI integration, participants generally show positive familiarity and the ability to utilise AI tools for academic purposes and knowledge development. However, moderate responses were identified in areas involving advanced AI applications, such as assessment, classroom management optimisation, and real-time feedback. Overall, the results indicate that prospective mathematics teachers possess foundational readiness to integrate AI into teaching practices, although further training and structured support are necessary to enhance advanced AI-based pedagogical integration.]]>
