[MD 2.0]②Smart Partner: How to Use 'AI'

Survival Strategies for MDs in the Age of AI
Multiple Inquiries to Generative AI
A Tool for Ensuring Objectivity

At the Noryangjin Seafood Wholesale Market located in Dongjak-gu, Seoul, Juyoung Lotte Mart and Super Customer Service Team Merchandiser (MD) is discussing a product planning proposal using AI with a partner company. Photo by Yejoo Han

Joo Jaeyoung, Merchandiser (MD) for the seafood team at Lotte Mart, recently planned packaging containers for an upcoming holiday gift set. Instead of asking the in-house design department for support, he directly input prompts into a generative AI tool to create blueprints and draft images. By instantly sharing these AI-generated drafts with partner companies, the repetitive revision process was significantly reduced. Joo stated, "In the past, I had to go back and forth with the design department many times, but by leveraging AI drafts, the time needed to develop a single product has been shortened by about three weeks to a month."

Hwang Hyoeun, MD at Lotte Homeshopping, also utilizes generative AI as a "tool for ensuring objectivity." While preparing to launch an overseas soda machine, she asked AI several times to verify the uniqueness of the gas injection technology proposed by a partner company. The AI provided information showing that the technology was similar to gas injection methods used in operating room resonant equipment and life vests, and this data was incorporated into summarizing the Unique Selling Point (USP) for the broadcast. Hwang said, "When you manage a product, it’s easy to lose your objectivity, but AI helps analyze a brand’s strengths and weaknesses coldly based on data."

All MDs in the Retail Industry Now Use AI

Generative AI is rapidly transforming how retail companies work. Merchandisers, who are responsible for every stage of retail from product planning and development, sourcing, cost negotiations, logistics, sales and promotion, to post-sales inventory management and withdrawal, are increasing productivity and reducing costs by making use of AI.

On July 15, The Asia Business Daily closely covered the daily work of MDs at department stores, hypermarkets, corporate supermarkets, e-commerce platforms, and home shopping channels, and found that the vast majority utilize generative AI for their core work.

For example, in the past, a supplier preparing to enter a home shopping channel needed to spend between 20 million to 30 million won to produce insert videos for product demonstrations. Recently, however, the use of generative AI has significantly reduced video production costs, making it much easier for small and medium-sized companies to approach home shopping. Hwang explained, "Listening to suppliers, video production costs have dropped by around 60% with AI. As cost burdens fall, more suppliers are proposing new brands and products, and from the perspective of MDs, the variety of products they can choose from is expanding."

The area changing most rapidly with AI adoption is fashion platforms. At Musinsa, MDs not only bring in global brands but collaborate from the product planning stage. They jointly discuss the structure and design concepts for exclusive capsule collections tailored to Musinsa customers. While in the past, brands would create products and distributors would simply sell them, the structure is shifting to distributors co-planning products together with brands.

Industry insiders describe this as the "Brand Developer" approach. The brand serves as a bridge to connect the tastes and trends of Korean consumers, while for consumers, it offers the new experience of products that did not previously exist.

Greater Use of AI in Processed Foods and Certain Categories... Potential Polarization by Category

However, AI does not change every merchandiser’s work in exactly the same way. Within the retail sector, there is a strong view that the impact of AI will differ significantly depending on the product characteristics, and a polarization by category is likely to emerge. In processed foods and daily essentials—where there is ample sales history and relatively predictable demand—substantial data-driven decision making is possible for sales forecasting, ordering, price management, and promotion analysis. As AI adoption advances, these categories are expected to see a significant reduction in repetitive work for MDs, with some suggesting that a single MD could handle a broader range of products.

An MD at a major retailer commented, "For categories like snacks or beverages where there is enough sales data, AI use will expand much more rapidly, and one person may manage multiple categories at once. On the other hand, for products that require the creation of a new market, people will inevitably need to think things through more deeply."

This content was produced with the assistance of AI translation services.