How does AI scale in the enterprise? Chris D’Agostino of FIS shares how large organizations are using LLMs, agentic workflows, and digital workers to modernize core systems and redefine how software gets built and delivered.
In this episode of Hybrid Minds, host Vahe welcomes Chris D’Agostino, Chief Data and AI Officer at FIS, for a wide-ranging conversation on the application of AI in enterprise environments. Chris draws on leadership experience from Databricks, Capital One, and FIS to unpack how large-scale financial platforms are evolving with LLMs, agent frameworks, and real-time decision engines.
Chris explains how his teams are deploying AI to refactor legacy systems, automate back-office operations, and develop agentic capabilities across global financial infrastructure. All while navigating compliance and risk. The conversation also explores deeper themes: the future of software as adaptive systems, the ethical limits of AI empathy, and how digital workers may reshape the future of labor itself.
This episode is essential listening for enterprise architects, engineering leaders, and AI strategists building intelligent systems at scale.
Key Quotes:
“It's more than just a clone, right? It's not just a clone of what its skillset is and what tool it has access to. It's a different worker altogether based on where the agentic workflows are failing or not being done as efficiently as possible. They're trying to scale up that way and say, ‘well, if we have a different worker that has, sort of, along the lines of the mixture of experts, right? Instead of it being really good at eight things, it's really, really good at one thing, and that's gonna increase the throughput for the overall workflow. So, it'll be fascinating to see where it goes.”
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