LG Energy Solution expands AI use, eyes 50% by 2028

LG Energy Solution, a South Korean battery maker, told employees on April 13 it will expand AI use across the company and now aims to lift productivity by 50% by 2028, up from a previous target of 30% by 2030, as global battery competition heats up.

CEO Kim Dong-myung said the company cannot match rivals through scale alone and will instead lean on its patents, nearly 30 years of accumulated industry expertise, and workers.

The company has set up a CEO-led AI governance committee for monthly reviews and plans to roll out an enterprise AI platform in non-sensitive areas first, while expanding employee training.

🔗 Source: The Korea Times

🧠 Food for thought

Implications, context, and why it matters.

LG’s AI push meets a changing battery market

LG Energy Solution is speeding up AI-driven productivity work as competition tightens around its battery plants.
Chinese rivals like CATL, the world’s largest electric-vehicle battery maker, have pulled ahead while South Korean manufacturers race to keep up with an unexpected market turn 1.
Demand is moving from premium nickel-based batteries, a South Korean strength, to lower-cost lithium iron phosphate (LFP) batteries where Chinese firms lead 1.
The shift has weakened South Korea’s largest battery makers in markets outside China 2.

AI is turning into a competitive lever for heavy industry

AI Transformation (AX) is spreading beyond digital services into factories and plants, and LG Energy Solution fits that pattern 3.
Petrochemical and energy companies use AI to organize manufacturing data. Many also use AI and digital twin-based platforms, software models that simulate real-world equipment and plants, to tune performance. Others use AI-enabled systems for safety work and regulatory compliance 3.
South Korea’s “6th National Standards Basic Plan (’26~’30)” backs AI-based and converged standards. It also aims for leadership in robotics and next-generation vehicles 4.
Manufacturers now pair AI with years of operating data and process know-how to raise productivity when scale alone falls short 5.