Why the Next Phase of Retail CX is Focused on the Agent Desktop

Retail has spent years perfecting the customer-facing chatbot. Faster replies, automated returns, instant order updates, and self-service tools designed to shorten the wait between a shopper’s question and an answer. Every holiday season brings another wave of investment toward the same goal, and retailers have made tremendous progress improving what customers can see. Now, as artificial intelligence absorbs more routine interactions, a new opportunity to improve customer experience (CX) and operating performance is opening up, starting with the agent desktop.

Human Agents Are Still the Biggest Cost … and the Biggest Opportunity

Frontline agent labor makes up 56 percent of total customer service costs, more than five times the next-largest category, according to our recent State of AI in CX Report. That single line item shapes the economics of the entire support operation, which means even small improvements in how efficiently agents work can move the needle across the whole budget.

This is where AI's role gets misunderstood. The industry has spent years optimizing AI to answer questions in place of a human. The more valuable question for retailers now is how AI can help the human agent handle every case faster and better. That's where most of the cost and most of the opportunity actually sit. Chasing containment rates alone misses where much of that spend lives.

Escalation is a Context Problem

Retail leaders tend to assume escalations mean an agent lacked the training to close the case. However, 73 percent of organizations say escalations caused by missing tools or incomplete customer history happen regularly, and 44 percent say poor handoffs remain a common issue in production AI.

When shoppers have to repeat themselves after an escalation, it means something in the context broke down.

This distinction matters when retailers decide where to put their next dollar. Training a support team to handle escalations better won't fix a context problem. No amount of coaching helps an agent who's starting from zero on a case that's already three touchpoints deep. Agents need the information to understand what has already happened and what needs to happen next.

Give Agents the Context They Need

Agent-facing AI closes that gap by surfacing account history, past interactions, and relevant policies before the interaction begins. Rather than reconstructing the customer’s experience from scratch, agents can move straight to resolution.

Michael Kors has already put this into practice and seen the impact. "Agent-facing AI has helped us be more efficient and deliver a consistent customer experience," says Ebrahim Hyder, the brand's vice president of customer service.

The benefit extends beyond faster resolution times. When agents have the right context readily available, they deliver a more consistent experience no matter who picks up the conversation. This matters enormously once holiday volumes climb and a brand can no longer rely on a handful of tenured agents to carry its reputation alone.

The Desktop Deserves the Next Investment

Deflecting volume away from human agents will always have a place, especially for the simplest, most repetitive requests such as order statuses, return eligibility, or shipping windows. Those cases are well suited to full automation, and retailers should keep pushing on them.

As those experiences become more efficient, the next gains will come from helping agents resolve more complex conversations, with complete context from the moment they engage. That's what lets a case close in one conversation instead of forcing the customer to start their explanation over.

Automation has made it possible to get customers answers faster. The next step is making sure the agent has the context to take the conversation the rest of the way.

Erica Clayton is head of sponsorships for ElevateCX and partnerships and CX at Forethought AI Agents by Zendesk.