Russia’s TMK rolls out LLM-based tools to digitize steel production data

TMK’s adoption of LLMs and generative AI inside heavy industry shows how quickly frontier capabilities are seeping into traditional sectors. Turning messy technical documentation and noisy workshop conversations into structured, searchable data is exactly the kind of embodied context AGI-like systems will eventually need to reason about the real world. For now, these deployments are narrow and supervised, but they lay the data foundations for more autonomous industrial agents later.

From a competitive standpoint, the key is that more firms outside tech are now building in-house AI tooling and data pipelines. As manufacturing, logistics and energy companies instrument their operations with AI, they generate proprietary corpora that could later feed specialized models or agent systems. That broadens the base of organizations with both the incentive and the expertise to push for more capable AI—often with different risk tolerances and safety norms than consumer internet platforms. Diffuse industrial adoption doesn’t move the AGI frontier overnight, but it gradually increases the number of actors with the data, capital and motivation to push those frontiers forward.