[DigitalToday reporter Dae-geon Seok] Posco Future M has moved to ramp up a companywide AI transformation (AX) to secure competitiveness in battery materials. Posco Future M said on July 28 it has set "Game Changer of the BoT (Battery of Things) ecosystem" as its digital innovation vision and established a companywide AX roadmap centred on process standardisation and data.

The roadmap, targeting completion in the first half of 2028, is structured to apply AI across the entire process from raw material procurement to product manufacturing and collaboration with customers. It set five key directions: optimising processes and systems using AI agents, building an integrated data hub, implementing AI-based intelligent factories, creating a hyperconnected system linking raw materials to products, and advancing R&D collaboration with strategic customers.

The goal is to raise productivity by 30 percent by making manufacturing processes more intelligent based on physical AI that combines physical environments and AI. In R&D, it plans to halve product development time by applying AI-based technology trend analysis and virtual verification. It also plans to double the speed of response to customers by automating quality analysis with robots.

It will also introduce AI simulation across order intake and marketing. It will shift to a structure in which AI analyses empirical data to support negotiation strategies from raw material price forecasts to customer demand outlooks and sales price negotiations. It plans to improve operational efficiency by integrated monitoring of the entire process from contracts, orders, production and shipment.

It will also use AI for energy management to automatically identify, diagnose and optimise inefficient equipment operation, building a system to cut energy use. It will also build in parallel a data platform to lead standards in a battery ecosystem expanding beyond electric vehicles to energy storage systems (ESS), robots and drones.

Posco Future M plans to apply AI agents by default to newly developed systems to minimise staff intervention. It also plans to train at least 1 AI-use specialist in each department within the year so they can directly lead the discovery and execution of AI projects.