
What happened
Posco Future M signed an agreement with Palantir to adopt its Foundry data analytics platform and Artificial Intelligence Platform (AIP), starting in sales and marketing before a phased expansion into manufacturing.
Why it matters
The deal aims to speed up decisions and automate routine processes so employees can focus on oversight, rather than manually coordinating fragmented data across sales and operations.
WHO IT HITSBattery materials manufacturers and their sales, marketing and production teams are the immediate focus, as Posco Future M first deploys Palantir tools in sales and marketing and considers later expansion into manufacturing and other operations.
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The Palantir agreement is the latest step in Posco Future M's broader push to embed AI across its operations. The battery materials maker unveiled its digital transformation strategy in July and launched a companywide AI innovation initiative in August, and this partnership builds on those earlier efforts by bringing in an external platform for data analytics and generative AI.
The initial focus on sales and marketing reflects a pragmatic sequencing: improve customer responsiveness and coordination before attempting to extend the same data-driven approach into manufacturing and other operations. By integrating fragmented data and embedding AI across workflows, Posco Future M expects to free employees from routine coordination and let them concentrate on oversight and final decisions, which is the mechanism behind its stated targets for faster product development and higher manufacturing productivity.
Over the longer term, the company intends to build a data-driven platform connecting production, sales and supply chain partners, a move that could strengthen collaboration across the battery industry and, in its telling, create new business opportunities. Alongside the technology rollout, Posco Future M is expanding employee AI training and testing staff-developed applications, with 87 employees who have completed specialist training working to identify inefficiencies and develop AI-based solutions, and selected projects set to roll out in phases by the first half of 2027.
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