Artificial Intelligence (AI) is a key driver of digital transformation in the banking sector, enhancing efficiency, risk management, and customer engagement. However, AI adoption remains constrained by technological, organizational, environmental, and customer-related challenges. This study introduces an Extended TOE-C Framework, expanding the traditional Technology-Organization-Environment (TOE) model by integrating customer-related factors to provide a more comprehensive assessment of AI adoption barriers in systemic banking institutions. Using a qualitative case study approach, the research analyzes AI adoption inhibitors within a systemic Greek bank, supported by secondary data from industry reports, financial analyses, and market observations. The findings identify seven key inhibitors across the TOE-C dimensions, emphasizing the need for strategic interventions in digital infrastructure, organizational culture, regulatory compliance, and customer trust. The study contributes to both academic research and banking strategy by offering a structured framework to guide AI-driven transformation in systemic banks.