The foundation of digital transformation in the AI era will hinge on clean data, according to Ben Xiang, Chief Technology and Strategy Officer at Sunwest Bank. Speaking with CIO Dive, Xiang emphasized that 2026 will mark a pivotal year as he implements the bank’s AI strategy, aimed at unlocking significant innovation potential within the industry.
Major financial institutions, including Bank of America, JPMorgan Chase, Goldman Sachs, and Citigroup, are making substantial investments in AI initiatives to transform workflows and enhance productivity. Sunwest Bank is pursuing similar ambitions this year, with a sharp emphasis on bolstering its data layer. “Ultimately, once you have the data in place, then you can start to automate things and leverage artificial intelligence to realize business value from that,” Xiang explained.
Sunwest Bank, a privately held commercial bank based in Sandy, Utah, appointed Xiang to lead its multiyear modernization initiative in September 2025. Having served on the bank’s board since 2015 and as interim CIO in 2019, Xiang is well-positioned to drive technology projects forward. Among these initiatives is the rollout of Microsoft Copilot, powered by OpenAI’s GPT-5 model, which aims to centralize information for employees by integrating publicly available and internal data.
The next critical element of Sunwest’s AI strategy involves creating a data lake to connect disparate data sources within the bank. Xiang stated that cleaning and centralizing the bank’s data will facilitate advanced data analytics, enabling more automation across its operations. “By doing this, we’re able to provide some pretty comprehensive and advanced data analytics that will enable a lot of automation that we’re looking to implement throughout the bank,” he noted.
Xiang’s overarching goal is to identify existing workflows that could benefit from automation while being cautious about investing in innovative projects that may not yield significant business results. With external research indicating that some generative AI projects have struggled to deliver ROI, he plans to focus on “low-hanging fruit” and initiatives with the highest potential for success within the organization. “We’re really looking to uplift the overall productivity and efficiency at the bank,” he added. Xiang intends to track various internal metrics over the next year to evaluate the success of the bank’s AI endeavors.
The banking sector is poised to capitalize on advancements in agentic AI this year, driven by improvements in large language models and the maturation of enterprise agent development tools, according to Accenture’s Top Banking Trends for 2026. Xiang highlighted that integrating large language models (LLMs) with other applications, along with the use of agentic AI, is where organizations are starting to uncover substantial value. “Being able to have an AI agent that can do multiple things, that can introduce intelligence to a workflow, has really opened up people’s eyes and opened up the doors for what you can do within an organization to dramatically improve efficiencies in a business,” he said.
An essential part of Sunwest’s strategy involves ensuring that staff members are equipped with the necessary tools and education to leverage AI effectively. Michael Abbott, senior managing director and global banking lead at Accenture, emphasized the importance of user-friendly AI agents for long-term success. “It has to be as easy as Excel or PowerPoint to use,” he remarked. “It can’t be a mystery novel.”
As Sunwest Bank embarks on this ambitious AI journey, it aims not only to enhance its operational efficiency but also to remain competitive in a rapidly evolving financial landscape. The integration of AI into banking workflows represents a significant shift, and leaders like Xiang are at the forefront of this transformation, seeking to harness technology for meaningful business outcomes.
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