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The foundation of digital transformation in the AI era starts with clean data. At least that will be part of the focus Ben Xiang, Chief Technology Strategy Officer, Sunwest Bank In 2026 he will develop an AI strategy.
“I think this is probably the most exciting time to be joining an industry that is poised for innovation with AI.” Sho said CIO Dive.
Big banks like Bank of America, JPMorgan Chase, Goldman Sachs, and Citigroup are investing heavily in AI initiatives aimed at transforming their workflows. Increase productivity and efficiency. Xiang said Sunwest Bank is pursuing similar goals this year with a focus on improving its data layer.
“Ultimately, once you have the data in place, you can start automating things and from there you can leverage artificial intelligence to realize business value,” he said.
Sunwest Bank is a privately held commercial bank headquartered in the United States. Sandy, Utah, tapped Sho guide it Multi-year modernization initiative and technology projects September 2025. Mr. Xiang has since also served as a member of the bank’s board of directors. He became CIO in 2015 and assumed the role of interim CIO in 2019. According to the press release.
Among the modernization efforts, Xiang said one of the bank’s projects is the deployment of Microsoft Copilot, which leverages OpenAI’s GPT-5 model. AI tools combine public and shareable information within the bank to provide employees with a central source of information.
The next element of a bank’s AI strategy revolves around connecting disparate data sources within the bank to a data lake. Xiang said cleaning up and centralizing bank data will enable advanced agent workflows in the future.
“By doing this, we will be able to provide fairly comprehensive and sophisticated data analysis, which will enable a lot of the automation that we are looking to implement across the bank,” he said.
In search of improved productivity
Ultimately, Xiang’s goal is to evaluate existing workflows that could benefit from automation and intelligence tools, while also ensuring that investments are not misallocated to innovative projects that “don’t deliver business results.”
Xiang said he is keeping an eye on external research that shows what kind of impact some companies are having. Generative AI projects aren’t tied to ROIThat’s why he plans to pursue “low-hanging fruit” and projects with the highest chance of success within the organization.
“We are serious about improving productivity and efficiency across the bank.” Sho Said. “There are a number of metrics that we will be looking at internally over the next 12 months to see if the AI projects we have embarked on are truly successful.”
The banking industry will leverage agent AI even more this year due to advances in large-scale language models and the maturation of enterprise agent development tools. Accenture’s key banking trends for 2026.
In fact, by connecting LLM to other applications and layering agent AI on top of that foundation, “people are really starting to see the value in it,” Xiang says.
“Being able to have AI agents that can do multiple things and bring intelligence into workflows has really opened people’s eyes and opened the door to what they can do within their organizations to dramatically improve business efficiency,” Xiang said.
Part of the bank’s success strategy is ensuring its employees are equipped with the necessary tools and educated about AI “to really put this amazing technology to work,” Xiang said.
Technology leaders need to make AI agents easier to use, especially for employees to achieve long-term success. Managing multiple agents I said I would work for them in the future. Michael Abbott is a senior managing director and head of global banking at Accenture.
“It has to be as easy to use as Excel or PowerPoint,” Abbott told CIO Dive. “That can’t be a mystery novel.”
