The purpose of this dissertation is to explore and examine the changes in ABB's business process automation, exploring the operational, planned, and structural consequences of ABB's implementation of artificial intelligence tools.The study will analyze the application of artificial intelligence (AI) tools and methods throughout ABB's divisions, along with their effect on business operations' rhythm, accuracy, and continuity of the company's internal processes. A contextual analysis of ABB's transition showed that AI has evolved from being a supporting tool, to fundamentally redesigning the architectures of core banking processes.We first describe the importance of this transformation in Azerbaijan's modern digital economy and the increased demand for transparency, agility, and customization of banking services. In a second step, we build upon ABB's transformation of service offerings and business operations and elaborate on the machine learning models, process automation systems, and adaptive analytics frameworks that influenced this transformation. It also considers the internal impacts such as faster processing, improved fraud detection, and redeployment of human resources to higher-value tasks.The case study can act as a roadmap for the implementation of responsible and scalable machine intelligence at financial institutions.