Manufacturers have invested heavily in forecasting, deploying new planning tools, analytics dashboards, and data lakes to analyze data coming from all directions—sales pipelines, supplier metrics, production schedules, logistics feeds. Yet, despite the analytics and dashboards, accuracy still slips. The problem isn’t a lack of data. It’s a lack of connection. Sales teams plan in CRM, operations in ERP, procurement in SRM, and logistics in WMS. Each function sees a part of demand, but no one sees the whole. When a major customer changes an order or a distributor delays a shipment, that signal takes days to ripple through the organization. By the time procurement adjusts or production recalibrates, the opportunity or risk has already passed. That’s why accuracy remains low even when data is rich. This latency in signal propagation directly impacts the bottom line; delayed responses contribute to an average inventory holding cost spike of 8-12% of COGS due to unnec...
For years, enterprises have tried to make customer service faster — automating workflows, tightening SLAs, launching 24/7 chatbots. Yet customers still wait — not only for responses, but for reassurance that someone understands. Speed alone doesn’t feel like care anymore. Because real-time isn’t defined by seconds — it’s defined by intelligence that understands intent and acts with empathy. That’s the new frontier of customer experience emerging through Agentic AI for customer service — a system of intelligent agents that doesn’t just respond instantly but reasons, learns, and collaborates with humans to make service truly real-time. Are We Solving Problems or Just Replying Faster? Most customer service journeys still begin the same way they did a decade ago — a ticket raised, a call logged, an email sent. Every step that follows is a reaction. Agentic AI for customer service redefines that flow. Instead of waiting for a customer to report an issue, intelligent agent...