General Background: The rapid development of artificial intelligence (AI) has introduced significant transformations in education, particularly in supporting teacher professional competence. Specific Background: AI is increasingly utilized in lesson planning, assessment, feedback, and administrative tasks, yet its integration into teacher professional development remains complex and context-dependent. Knowledge Gap: Existing studies predominantly focus on student outcomes or teacher perceptions, with limited synthesis addressing strategies, challenges, and systemic factors influencing AI integration for teacher competence. Aims: This study aims to synthesize forms of AI utilization, integration strategies, and implementation challenges in strengthening teacher professional competence through a Systematic Literature Review approach. Results: Findings indicate that practice-based professional development is the most consistent strategy, while AI literacy, self-efficacy, and policy support act as key mediating factors; major challenges include literacy gaps, ethical concerns, inadequate infrastructure, and limited policy alignment. Novelty: The study proposes a synthesis framework positioning AI as an object whose effectiveness depends on pedagogical, psychological, and structural policy factors rather than as a standalone technological solution. Implications: The results highlight that strengthening teacher professional competence requires a systematic process integrating teacher readiness, contextual training, and institutional policy support, emphasizing that AI adoption must be aligned with broader educational systems. Highlights• AI utilization centers on planning, assessment, feedback, and administrative support• Practice-based training demonstrates consistent outcomes in competency development• Integration depends on literacy, self-efficacy, infrastructure, and policy alignment KeywordsArtificial Intelligence; Teacher Professional Competence; AI Literacy; Professional Development; Systematic Literature Review