As a leading financial institution with around $2 trillion in assets under management, Mizuho Financial Group plays a critical role in global capital markets. Its U.S. arm, Mizuho Americas, supports a wide range of services in corporate and investment banking, securities, and capital markets, serving Fortune 500 clients and institutional investors. 

In the first part of the series, JC Lionti, Chief Data and Analytics Officer, Mizuho Americas, in conversation with Informatica’s Amy McNee, examined how Mizuho is translating AI potential into practical business value, rethinking GenAI’s role, aligning stakeholders, and redefining the modern data leadership function.

Building on that, the second part explored how the bank is developing a conservative yet forward-looking AI governance framework — one designed to ensure innovation progresses in step with evolving regulatory and ethical expectations.

This final part covers the evolving landscape of AI regulation, pragmatic advice for organizations starting their AI journey, and the importance of responsible AI that serves tangible business value.

Wrestling with a fragmented regulatory landscape

The surge of AI innovation has outpaced regulatory harmonization, and Lionti is forthright about the challenges it poses. “A lot of regulations are still new or evolving,” he explains.

Currently, Lionti and his team are working closely with Mizuho’s legal department and other partners to understand how to operationalize AI within the shifting compliance framework. “We’ve not been able to fully resolve all issues yet. We’re on our way.”

The complexity lies in aligning AI model deployment with jurisdictional legalities. “It’s more a question of what model or solution we can make available in which jurisdiction,” he explains.

Despite ongoing efforts, he anticipates regulatory divergence rather than convergence, at least in the near term.

Balancing speed and risk

When asked what advice he would give to a company embarking on an AI or data governance program, Lionti says, “Learn how to manage the multiple conflicting voices that you’re going to hear.”

He describes the tension between innovation-driven urgency and risk-averse caution that most organizations encounter. On one side are those pushing to “move fast” and “keep up.” On the other side are voices saying, “It’s just too risky” or “It’s too expensive.”

To reconcile these forces, Lionti urges a clear-eyed focus on business value. “Developing an AI solution is not going to get you anywhere,” he states. Instead, he recommends treating AI as “part of the solution toolkit that will help solve business problems.”

This solution-oriented mindset is already transforming how Mizuho’s data and analytics teams operate. “We’ve merged our analytics practices with the AI program to create a solution organization,” he shares.

This integrated approach focuses on analyzing business pain points and selecting the appropriate technology — whether it’s AI, traditional analytics, or even simpler tools — to solve them.

The case for responsible AI

Resonating deeply with the idea that not every problem demands a high-powered AI solution, Lionti says, “Doing AI for AI is destroying value. It’s not creating value.” For him, value creation is the ultimate litmus test: “AI for creating business value is what you have to aim for.”

He concludes with a balanced view of AI’s potential: “AI can bring a lot of value and can make all of us much more efficient, but again, AI for AI is not the answer.”

CDO Magazine appreciates JC Lionti for sharing his insights with our global community.