POSCO Future M to Drive AI Manufacturing Innovation: "30% Productivity Boost by 2028"

Planned Completion by First Half of 2028

Halving Product Development Lead Time

Aiming to Double Client Response Speed

POSCO Future M is embarking on AI-based manufacturing innovation to enhance its competitiveness in the battery industry. The company plans to integrate artificial intelligence (AI) into the entire process, from raw material procurement to production and collaboration with clients, with the strategy of boosting productivity and quality competitiveness.

On the 28th, POSCO Future M announced that it has presented "Battery Object Ecosystem (BoT), Game Changer" as its vision for digital innovation and established a company-wide artificial intelligence transformation (AX) roadmap centered on process standardization and data-driven strategies.

POSCO Future M has presented its digital innovation vision, the "Battery Object Ecosystem (BoT), Game Changer," and is promoting an enterprise-wide artificial intelligence transformation (AX). POSCO Future M

The company intends to incorporate data-driven AI across all stages including raw material procurement, product manufacturing, and collaboration with client companies. Its core strategic directions are: ▲ optimizing processes and systems through AI agent integration, ▲ accelerating intelligence based on an integrated data hub, ▲ realizing intelligent factories leveraging AI, ▲ building an intelligent hyper-connected system from raw materials to finished products, and ▲ advancing strategic research and development (R&D) collaboration with key clients.

POSCO Future M plans to complete its manufacturing innovation initiatives by the first half of 2028. Through this, the company aims to achieve "physical AI-based" intelligence in manufacturing processes, increasing production efficiency by 30%. The goal is to reduce product development lead time by half compared to current levels by applying AI for technology trend analysis, design, and virtual verification.

The use of automation, such as quality analysis robots, will double the speed of root cause analysis and response to quality issues, thereby significantly improving responsiveness to client companies.

AI will also be actively employed in orders and marketing. By introducing AI simulations into every step from raw material price prediction to client demand forecasting and sales price negotiations, POSCO Future M will enable data-driven contract negotiations. This allows for integrated monitoring of the entire process—contracts, orders, manufacturing, and shipping—to optimize operations.

From the perspective of ESG management, AI will be used to optimize facility operations. The company plans to automatically identify and diagnose inefficient facility operations, suggest optimal operating conditions, reduce energy consumption, and improve operational efficiency.

Through AI-driven manufacturing innovation, POSCO Future M aims to increase customer trust in product quality and manufacturing competitiveness, thereby establishing a virtuous cycle that expands orders and attracts new client companies.

Furthermore, by leveraging the data accumulated throughout the production, management, and sales process, POSCO Future M envisions building a platform to set the standard within the expanding battery ecosystem—including electric vehicles, energy storage systems (ESS), robots, and drones—and to create new business opportunities.

Going forward, the company plans to systematically apply AI agents to all newly developed systems to minimize staff intervention. Additionally, within this year, it will cultivate at least one AI expert per department, empowering them to spearhead the identification and execution of AI projects, thereby promoting the broad adoption and institutionalization of AI manufacturing innovation outcomes.

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