Dilip Venkatachari came to banking from Google and PayPal, where moving fast was the default and scaling meant adding servers. As SEVP and Chief Information and Technology Officer at U.S. Bank, he now runs technology for an institution built on decades-old core systems where the data is people's money, and his team is moving agentic AI out of the experimentation phase and into how the bank actually operates.
Dilip explains why he held off on productivity metrics during the bank's AI rollout and let teams run their own experiments first, why the real work of scaling AI turned out to be data, identity, security, and observability rather than model selection, and how he modernizes legacy systems by hollowing out the core in business-driven chunks instead of attempting a risky rip-and-replace. He also makes the case that banking's heavily codified procedures, from KYC to disputes, are unusually well suited to agents.
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3 Takeaways:
- Why Dilip's team launched "Let a Thousand Flowers Bloom" and deliberately skipped productivity metrics early, to avoid rewarding behaviors nobody understood yet.
- How U.S. Bank treats data, identity, integration, and observability as the real bottleneck to scaling AI, with the goal of making each new use case cheaper than the last.
- Why Dilip argues banking's codified procedures, from customer onboarding and fraud checks to dispute management, give agentic AI clear control points and a clear definition of what good looks like.
Chapters:
(00:00) Introduction
(02:09) Dilip's Career Path
(03:34) Tech Scale vs. Bank Scale
(05:39) Innovation With Control
(08:24) What CIOs Actually Prioritize
(10:44) Scaling AI Use Cases
(11:42) Agentic AI in Banking
(14:13) Managing the Human Side of AI Adoption
(16:10) Evangelize, Then Experiment
(17:58) AI Plumbing & Security
(18:43) Cybersecurity Group Therapy
(22:59) Modernizing Legacy Systems
(27:47) Leadership Lessons at Scale
About Dilip:
Dilip Venkatachari is Senior Executive Vice President and Chief Information and Technology Officer at U.S. Bank, where he is responsible for global technology infrastructure, security, products and services, and digital and technology transformation. He also serves on the board of U.S. Bank Europe. Dilip joined U.S. Bancorp in 2018 and joined the company's executive leadership team in 2023. In 2026, he was named one of American Banker's Most Innovative People in Finance for his work developing agentic AI and digital-asset infrastructure across the bank.
Before U.S. Bank, Dilip held senior executive roles at Google and PayPal/eBay, and spent time at McKinsey & Company helping large U.S. and international banks accelerate their digital transformations. He also co-founded and led three startups — Compass Labs, CashEdge, and CommerceSoft. Dilip holds an MBA from Harvard Business School and master's and bachelor's degrees in electrical engineering from Rice University and the Indian Institute of Technology, respectively. He holds more than a dozen U.S. patents.
Guest Highlights:
"The hardest part here isn't proving that it works. The hardest part is how do you scale it? How do you industrialize it?"
"If we put productivity metrics, speed metrics right now, there's a risk we are creating incentives for behaviors which we don't quite understand."
"AI for us is not just another technology program. It's a new way of building and running the bank."
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