Mitsubishi UFJ Financial Group (MUFG), one of Japan’s largest banking institutions, is undergoing a significant transformation by integrating artificial intelligence (AI) across all facets of its operations. This initiative is not merely about digitizing existing processes but aims to revolutionize the organizational structure by adopting AI agents to work alongside human employees.

Morito Emi, the head of MUFG’s digital strategy division, articulated this vision during the MUFG Fintech Festival held in Singapore. He emphasized that the goal is to evolve MUFG into an AI-native company, where AI plays a central role in the execution of various tasks and functions within the bank.

Despite deploying AI tools throughout the organization, Emi noted that only about half of the employees regularly engage with these technologies. To bridge this adoption gap, MUFG is intensifying its focus on three essential strategies: promoting company-wide AI training, establishing a robust architecture for AI agents, and redefining its data strategy to enhance accessibility for these AI systems.

Launched in July 2025, the “Hello AI @ MUFG” campaign aims to embed AI into the company culture. This initiative kicked off with a prompt challenge, where over 6,000 employees competed to create the most effective generative AI instructions, showcasing the bank’s commitment to fostering an AI-centric workforce.

Collaboration is a pivotal part of MUFG’s approach to enhancing its AI capabilities. In October 2024, the bank partnered with OpenAI to provide its employees access to ChatGPT Enterprise. This partnership is intended to facilitate the development of advanced AI applications and ensure dedicated support from industry experts.

Moreover, MUFG established a significant three-year partnership with Sakana AI, a rapidly growing Japanese AI startup that achieved unicorn status within a year. This alliance focuses on refining decision-making processes, with their inaugural project set to produce an AI-powered loan expert, designed to provide better recommendations and adapt through human feedback.

Currently, MUFG is executing approximately 60 advanced AI use cases within its operations, which are projected to save around three million work hours annually. For instance, one innovative application generates proposals for corporate clients, allowing bankers to dedicate more time to relationship-building activities.

Another noteworthy integration is the AI-based mergers and acquisitions matching function, which assists analysts in identifying potential acquisition targets that might be overlooked. Meanwhile, the bank’s trust banking division employs an AI document reader that extracts information from intricate legal and financial documents, thereby saving thousands of hours that staff would otherwise spend manually gathering data.

Looking ahead, MUFG has ambitious plans to enhance its offerings further, including a goal to triple the number of online small-business loans serviced by fiscal year 2026. This will be achieved through the implementation of AI for credit analysis, streamlining the approval process, and increasing accessibility for small enterprises.

In conclusion, MUFG’s strategic pivot towards becoming an AI-native organization illustrates its commitment to not only enhancing operational efficiency but also transforming the role of AI in banking. By prioritizing employee training, fostering collaborative partnerships, and embedding cutting-edge technology into its business model, MUFG is setting a paradigm for how financial institutions can leverage AI to achieve significant advancements.