Pradeep Karpur

Partner

Technology Consulting - Data and Analytics (EY)

Rather than bolting on isolated AI use cases on legacy processes, leading organizations are redesigning critical processes—such as order-to-cash, demand planning, or risk management—so AI agents are accountable for specific outcomes like revenue protection, cost reduction, or cycle-time improvement. These agents operate within defined guardrails, use enterprise data to make decisions, and trigger downstream actions, with humans focused on oversight and exceptions.

This shift requires treating AI as part of the operating model, not just a technology capability. When processes are designed this way, organizations create repeatable patterns for deploying AI across domains, shortening time-to-value and making results easier to measure and govern.

In this session, we will share a practical approach to building toward an AI-native enterprise, including how to identify the right processes to redesign, how to link AI initiatives to measurable business outcomes, and how organizations are scaling agentic AI beyond pilots into core operations.