KT, NongHyup, and Microsoft team up to bring agentic AI to retail customer service

KT, NongHyup Economic Holdings, and Microsoft Korea signed an MOU on Nov. 18 to deploy AI customer service and marketing systems across NongHyup's retail businesses, including agentic AI for order and delivery inquiries.

Categorized in: AI News Customer Support
Published on: Aug 18, 2026
KT, NongHyup, and Microsoft team up to bring agentic AI to retail customer service

KT, NongHyup Economic Holdings, and Microsoft Korea signed a memorandum of understanding on November 18 to deploy AI-powered customer service and marketing systems across NongHyup's retail and food businesses. The deal includes agentic AI services that can handle customer inquiries, order confirmations, and delivery notifications without human intervention.

The partnership centers on the three companies' existing work together: KT completed the public cloud migration of NH SingSing Mall, NongHyup's online agricultural marketplace, earlier this year. The platform moved from on-premises systems to Microsoft Azure and has operated stably since launching customer-facing services in July.

That migration was one of the largest Azure projects in South Korean e-commerce. The new agreement builds on it to expand AI use beyond infrastructure into daily operations of the marketplace.

What the AI services will do

NongHyup Economic Holdings will deploy customized recommendation and marketing systems that draw on customer, product, and order data across its retail and food divisions. The "agentic AI" services will handle customer inquiries, order tracking, and delivery notifications without a human agent in the loop.

KT will lead the development of AI transformation initiatives and oversee contact center construction and operations. NongHyup will provide operational data and testing environments based on its field operations; Microsoft Korea will supply the Azure-based AI tools and cloud infrastructure.

The three companies agreed to also explore new AI business opportunities in e-commerce, advance data-driven marketing, and internalize AI capabilities across relevant business units. For customer support teams, this means a concrete division of labor: KT builds the contact center tech, NongHyup runs it on real customer data, and Microsoft provides the infrastructure.

Fielding AI in real customer interactions

Park Sang-won, Executive Vice President and Head of KT's AX Business Division, said, "The successful public cloud migration of NH SingSing Mall marks the starting point for AI-driven retail innovation. Together with NongHyup and Microsoft Korea, we will develop new AI business models in the retail sector."

The companies have not announced a timeline for rolling out the agentic AI services. They also have disclosed no specific metrics for expected operational improvements or customer satisfaction targets.

For customer support teams, the practical implications are direct: AI agents will take over the routine front-line work of answering order-status questions, confirming purchases, and sending delivery updates. That shifts human agents toward complex inquiries the AI cannot handle - the kind that need judgment, empathy, or account-specific context.

An AI Contact Center for ongoing customer service functions means supervisors will need to monitor and manage a hybrid human-AI workflow. Much of that work is now routine: vendors such as KT are increasingly standardizing these kinds of front-line automations.

Why this matters for Customer Support

This is the kind of deployment that changes what a customer support team's daily workflow looks like. It automates order management, tracking, and update notifications - the highest volume, lowest complexity of your team's daily work. That leaves humans handling issues that actually need them: complaints, complex troubleshooting, and conversations involving accountability.

You don't need to work at NongHyup to see where this is going. The KT-Microsoft-NongHyup structure shows a pattern about vendor relationships with AI, and support leaders should know: realistic expectations. Plan staff training plus supervision around a hybrid model. Start by knowing how your platform handles the plain, routine inquiries that takes up most of your hours. The teams that work with their current AI tools to fine-tune escalation paths will make a stronger case for keeping human agents for the work that requires them.


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