GlobalData has hosted a new expert roundtable examining the real-world opportunities and challenges of applying agentic AI in banking and financial services. The session, titled “Agentic AI in Banking & Financial Services: Beyond the Hype,” brought together Jeff Veis, Chief Marketing Officer at Impetus Technologies; Deepak Khosla, Chief Growth Officer & Head of AI Business at Impetus Technologies; and Stephen Walker, Retail Banking Analyst at GlobalData.
The discussion moved quickly beyond industry hype to explore why many financial institutions are experimenting with agentic AI, yet relatively few have deployed it at scale. The participants identified several areas as key barriers to production adoption including lack of data readiness, fragmented enterprise context, governance gaps, safety risks and regulatory expectations.
Speaking at the event, Khosla stated: “An agent in banking is not just summarizing a document. It could influence and impact credit, fraud, payments, customer treatment, reporting, or advice. The bar for production is therefore much higher in the banking and financial services sector.”
He emphasized that successful agentic AI adoption depends on building strong AI-ready data foundations and grounding AI agents and systems in proprietary business processes, operational realities, historical interactions and governance policies.
“Our approach starts with the belief that agentic AI success depends on the quality of enterprise context available to agents. If that context is fragmented, stale or poorly governed, they will fail in production.”
The session concluded that financial institutions should focus on engineering enterprise context by building trusted semantic layers, ontologies, and knowledge graphs that AI agents can reliably reason over. This will enable them to power strategic high-impact use cases where ROI is measurable and risk can be managed.
To learn why context engineering is essential for safe, effective deployment of agentic AI in financial services, view the full roundtable here:
