LG Energy Solution is accelerating a transformation of its battery research and development system by combining AI agents with automated experimentation.
According to the company on July 26, it is using AI agents at the materials-development stage to identify new candidate materials and optimize their performance. AI is also being applied to analyze customer requirements, support cell design, interpret test results, and build prototype development schedules.
The approach allows AI to handle repetitive data analysis and documentation, enabling researchers to focus on technical validation and key decision-making. LG Energy Solution is expanding AI from selected support functions—such as price forecasting and safety diagnostics—into day-to-day R&D operations.
The need for AI-driven R&D and systematic patent management is growing as the company broadens its technology and product portfolio. Its focus now extends beyond next-generation technologies such as all-solid-state batteries, lithium manganese-rich (LMR) cathode materials, dry electrodes, and sodium-ion batteries to products for AI data centers, energy storage systems (ESS), humanoid robots, and other robotics applications.
LG Energy Solution has developed specialized models to analyze battery characteristics that general-purpose AI models struggle to predict, including gas generation and ionic conductivity. The models are being used to identify promising electrolyte molecules. Once AI narrows the candidate pool, automated equipment produces electrolyte formulations and measures their properties, with the results fed back into the training data.
At the cell-design stage, the company uses AI to identify materials and design parameters suited to target performance specifications. It is also applying technology that predicts long-term battery life and the risk of sudden performance degradation using only early charge-discharge data.
LG Energy Solution aims to establish an R&D system that can either cut development time in half or complete the same research workload with roughly half the resources.
For enterprise use, the company is primarily deploying LG AI Research's large-scale AI model, EXAONE. It is also introducing an enterprise AI platform in phases, beginning with areas not directly related to national core technologies, linking internal data with operational systems.
Potential security risks and organizational changes arising from AI adoption are being reviewed directly by the chief executive. LG Energy Solution CEO Kim Dong-myung chairs a monthly AI Governance Committee to discuss and support the rollout of new AI solutions, information security, and change-management issues.
“AI is more than a tool for accelerating R&D—it is a core technology that will drive innovation across our research and development,” an LG Energy Solution official said. “We will strengthen our future technology competitiveness through AI transformation.”
