As one of the biggest financial institutions in the U.S., Capital One isn’t running away from generative AI and agentic AI. Instead, the $490 billion company is using the technology to enhance both internal operations and customer experience. In this Targeting AI episode, the chief scientist and executive vice president at Capital One discusses some of the challenges and opportunities the financial giant is facing in customizing LLMs, and how the company continues to prioritize risk management and safety.
Featuring: Prem Natarajan, executive vice president, head of enterprise AI and chief scientist, Capital One
In today's episode, we cover:

Capital One's enterprise AI strategy is focused on creating customizable platforms using open source or open weight models
Capital One uses its proprietary data to customize AI models
The company uses GenAI and agentic AI for internal operations, such as with agent assist tools for customer service and customer-facing experiences like chat concierge
The enterprise has a focus on long-term transformation and not short-term ROI

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References:

Capital One AI partnerships aim to build trust and grow talent
Compare proprietary vs. open source for enterprise AI
The importance and limitations of open source AI models

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