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POSCO Future M held an AI Festival at POSTECH in Pohang to showcase results from its employee-driven “AI 100-Day Challenge” competition, recognizing 28 outstanding projects. The grand prize went to a model that predicts heater failures in cathode material kilns before they occur, while an AI-based MRO procurement system and a scanning electron microscope analysis automation program took top excellence awards. Selected projects will undergo field testing and be deployed to actual production sites by the first half of next year. The company aims to build an “AI Native” operating framework where AI handles work planning and execution while employees focus on final judgment, targeting a 30% improvement in manufacturing productivity and a 50% reduction in product development time by the first half of 2028.
Key Elements
POSCO Future M (003670.KS) is deploying AI systems developed by its own employees to production sites as part of a push to strengthen manufacturing competitiveness. The South Korean company announced on October 14 that it held an “AI Festival” at POSTECH in Pohang, North Gyeongsang Province, on October 13 to share in-house AI achievements and recognize 28 outstanding projects.
The event marked the final presentation of results from the “AI 100-Day Challenge,” a three-phase program that ran since June. Awards were given in two categories: AI app development for office and manufacturing tasks, and AI video production for internal communications, safety, and training. Selected projects will undergo field testing and employee feedback collection before being applied to actual operations and production sites by the first half of next year.
The grand prize went to the “Kiln Heater Condition Prediction Model,” which predicts failures in kilns—critical equipment in the cathode material manufacturing process. Kilns are heat-treatment facilities that process cathode material raw materials at high temperatures, and maintaining consistent internal temperature is key to product quality and production stability. The model is designed to automatically collect and analyze heater operating data, calculating failure risk levels and inspection priorities. By identifying equipment anomalies in advance and efficiently determining inspection and replacement timing, the system can reduce emergency repairs and production disruptions.
Top excellence awards went to the “AI-Based MRO Material Integrated Management and Intelligent Procurement System” and “SEM Data Unmanned Acquisition and Analysis Automation.” The procurement system uses AI to search material information scattered across multiple systems and recommends purchasable items and South Korean-made substitute products. The SEM automation program automates the entire process from product particle imaging to size and shape analysis and result generation, reducing repetitive work in electron microscope imaging and data organization while improving accuracy. SEM refers to a scanning electron microscope that magnifies the fine structure of objects to measure size and shape.
POSCO Future M plans to use this event as a springboard to fully build out its “AI Native” work framework. The structure envisions AI handling everything from improvement planning to execution—going beyond simple repetitive task support—while employees focus on final judgment and decision-making.
Company-Wide AI Transformation Roadmap
The AI Festival is part of POSCO Future M’s company-wide AI transformation (AX) strategy. In July, the company unveiled its digital innovation vision as a “Battery of Things (BoT) Ecosystem Game Changer” and established a mid-to-long-term AX roadmap. The core thrust is applying AI across the entire value chain, from raw material procurement to product manufacturing and R&D collaboration with customers.
Specific targets were also laid out: a 30% improvement in manufacturing productivity and a 50% reduction in product development time by the first half of 2028. In September, the company held a kickoff event for process innovation (PI)-based AX projects, sharing detailed initiatives for applying AI across manufacturing, R&D, and marketing functions.
The company is also cultivating in-house AI specialists. In July, it announced plans to train at least one AI application expert per department by year-end, tasking them with identifying and executing projects. The outstanding cases from this challenge are expected to serve as a catalyst for company-wide adoption.
Strengthening Competitiveness in Secondary Battery Materials
The expanded AI adoption comes amid intensifying competition in the secondary battery materials market. Cathode material is a core component that determines electric vehicle battery performance and cost, and even minute temperature deviations in the manufacturing process directly affect product quality. AI systems that detect equipment anomalies in advance—like the kiln heater prediction model—can directly improve yield and maintain utilization rates.
POSCO Future M is South Korea’s largest cathode material producer and is expanding its production footprint overseas, including in North America and Europe. A standardized operating system with AI integrated into manufacturing processes can be applied identically to overseas plants, giving the company an advantage in ensuring quality uniformity across its global production network. This is the backdrop for the company’s accelerated push to build an AI Native framework.
Industry observers note that AI adoption among battery material companies is emerging as a key factor in customer certification response and quality competitiveness, going beyond simple cost reduction. Particularly as the EV chasm (temporary demand slowdown) makes cost competitiveness through manufacturing efficiency increasingly critical, POSCO Future M’s latest move is being interpreted as a proactive investment in response to shifting market conditions.
