For the past decade, customer service artificial intelligence has been stuck in a pattern of polite helplessness. Many organizations have deployed sophisticated voice assistants that understand emotion, intent, and natural language, yet when a customer calls about a delayed shipment, the AI still hits a wall. It can empathize, but it cannot act. It logs a ticket, promises a callback, and moves on. The conversation succeeds, but the resolution fails.
This is the service gap. It is the disconnect between the front office that talks to customers and the back office that actually moves inventory, reroutes shipments, and resolves exceptions. In 2025, companies are finally bridging that divide. We are shifting from conversational AI, which specializes in understanding language, to agentic AI, which specializes in taking action.
Contrary to common fears, this shift does not remove the human. It elevates the human into a strategic role. Agentic AI gives people the operational reach they never had by handling the execution work across CRM, enterprise resource planning, and warehouse systems.
A typical service failure starts long before a customer ever picks up the phone. Imagine a manufacturing client waiting for a critical component. A weather event delays the package. The customer calls support. The service agent can see the delay but cannot fix it. The agent cannot reroute a shipment, release inventory from another warehouse, or trigger a priority pick without navigating a maze of internal approvals. She spends more time negotiating internal systems than helping the customer.
This is not a people issue. It is a systems issue. CRM, ERP, and warehouse platforms operate on separate islands. The human wants to solve the problem but has no hands inside those systems.
Agentic AI changes this dynamic. Instead of only predicting the next word in a sentence like a traditional language model, the agent predicts the next action in a workflow. It can use tools, connect systems, and execute tasks.
In the delayed shipment scenario, an agentic system works alongside the service rep as a real collaborator. The system notices the weather delay before the customer calls. It checks enterprise systems and identifies alternative inventory sources. When the agent opens the customer profile, the AI offers a clear option. "Your shipment is delayed. I can reroute from Dallas using priority delivery. Estimated cost: 45 dollars. Approve?" When the human approves the decision, the agent executes the operational steps across logistics systems automatically and confirms the new tracking information to the customer. The human makes the judgment call. The agent handles the work. This balance is what companies have been missing.
The Two Tier Collaboration Model
This emerging partnership creates a new operating structure.
Tier 1: The Agent as Executor
The AI agent handles the horizontal complexity. It integrates data across systems, synchronizes changes, and ensures that promises made in the contact center are fulfilled in operations. It is responsible for speed, accuracy, and repeatability.
Tier 2: The Human as Strategist
Humans provide vertical decision-making. They understand context, long-term relationships, and business nuance. Should a company spend $45 to expedite a $50 part? A machine might decline. A human considers lifetime value, account sensitivity, and long-term retention. In this model, humans no longer chase simple status calls. They supervise higher-level exception dashboards and intervene when a situation requires judgment, negotiation, or empathy.
As multimodal AI systems advance, this collaboration will increasingly be driven by voice. Logistics managers, planners, and supervisors will interact with their enterprise systems conversationally. "Show me all shipments stuck in the Northeast and reroute high-priority clients to Atlanta." The Agent parses intent, identifies high-priority accounts, checks inventory levels, and executes the required transfers. Voice becomes the interface. The agent becomes the operator. The human sets the strategy.
Closing the Loop
For too long, companies have treated customer service and supply chain operations as separate functions. One apologizes for problems it cannot fix. The other fixes problems it never knew a customer complained about. Agentic AI closes this loop. It creates a unified system of action where human judgment and machine execution work together. By combining strategic supervision with automated operational follow through, companies can finally deliver what customers expect every time: the right product, at the right place, at the right time.
The companies that win will not be the ones with the best chatbots. They will be the ones that pair human intelligence with AI systems that can act, not just talk.
Ankit Talwar is director of product management for AI at Dell and a distinguished fellow of the Soft Computing Research Society.