Enterprise AI has moved beyond chatbots and co-pilots. Agentic AI systems now autonomously orchestrate multi-step workflows — ingesting documents, extracting entities, validating outputs, and escalating to humans when confidence thresholds aren't met.
But autonomy without governance is a liability, especially in regulated industries.
This session examines real-world agentic AI architectures deployed in financial services — covering multi-agent pipeline design, human-in-the-loop escalation patterns, PII handling, hallucination detection, and audit-ready output generation. The focus is on what it takes to move agentic AI from impressive demo to production-grade enterprise system that compliance teams, auditors, and leadership can trust.
Practical takeaways for architects, engineers, and business leaders thinking about where agentic AI fits — and where it still needs a human in the loop.