October 30, 2026, (Inside AI) — Japanese credit card issuer Credit Saison has reported a 954% return on investment from a month-long pilot of ChatGPT Enterprise, a figure that more than doubles its initial target and has prompted a companywide rollout within weeks. The pilot, which ran from late June to early August 2025, involved 315 employees and saved each participant an average of 14 hours per month, or roughly 169 hours annually. Credit Saison announced the results this week, positioning the deployment as a case study in how mid-sized financial firms can measure and scale generative AI.
The company, which serves approximately 31.16 million cardholders and employs about 3,700 people in Japan, launched the pilot with volunteers, executive nominees, and every executive including the president. That group represented just under 10% of its domestic workforce. The results exceeded internal targets of 500% ROI and 7.5 hours saved per person per month. In a post-pilot survey, 75% of managers and 70% of nonmanagerial employees said they could not do without ChatGPT Enterprise. Approximately 80% of legal department respondents reported an improved ability to do their jobs, while more than 80% of IT staff reported greater job satisfaction.
Credit Saison's approach stands out for its emphasis on leadership participation. Kazutoshi Ono, Senior Managing Executive Officer, CDO, and CTO, set the tone early. "We won't know until we really put it to work," Ono said, according to company statements. He then encouraged Katsumi Mizuno, Representative Director, Executive President and COO, to lead by example. "It's not enough to encourage employees to use it. Leaders need to use it regularly themselves," Ono told Mizuno. Mizuno built his own custom GPT for company research and incorporated it into daily work. That visible executive use helped bridge the gap between pilot results and a swift companywide approval.
The pilot's success also relied on a dedicated Slack channel run by Credit Saison's Center of Excellence, where employees shared successes and failures openly. OpenAI provided training for executives and practical workshops for beginners. One standout use case was a custom GPT that simulated shareholder meetings using voice mode. Employees rehearsed realistic exchanges, and the tool drew strong interest from senior leadership, spurring broader adoption of voice-based AI.
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Beyond the pilot, Credit Saison reports that its engineering team's use of Codex saves an average of 850 hours of work each month. The company now frames its AI strategy around three dimensions: Employee AX, which changes how employees work; Customer AX, focused on improving customer experience and interfaces; and Corporate AX, which rethinks organizational structures and roles around AI. An in-house AI call center is under development for Customer AX, while Corporate AX remains at an earlier stage of identifying applications.
Credit Saison's results arrive as enterprises increasingly demand hard numbers from generative AI investments. Many pilots stall because firms cannot translate time savings into financial returns or because leadership remains passive. This case suggests that executive modeling and open experimentation can accelerate adoption. The 954% ROI figure, while self-reported and based on a short pilot, provides a concrete benchmark that other financial institutions may try to replicate. It also highlights a shift from general-purpose chat use to custom GPTs tailored for specific workflows like sales debriefs, prospect roleplay, and shareholder meeting preparation.
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The company is also considering ChatGPT Work to help employees focus on higher-value tasks. As AI takes on more autonomous functions, Credit Saison plans to tighten security with customer information protection as a prerequisite. "We can't stop at Employee AX. The challenge ahead is how far we can progress toward Corporate AX, redefining our organizational design and the division of responsibilities with AI as a starting point," the company stated. Credit Saison's relationship with OpenAI remains central to that progress, with plans to evaluate new capabilities and deploy them quickly once safety is established.
