Industrial AI scaling depends on interoperable operating architecture
Industrial AI becomes operationally material when it can move across plant systems, enterprise workflows and supply-chain decisions without being trapped by proprietary control-system boundaries.
ARC India Forum’s industrial-AI recap points to a shift from pilots toward production-grade operations, where interoperability and control-system openness become operating-model requirements.
The affected decision is whether AI output can safely influence production, maintenance, quality or supply actions. Value requires interoperable architecture, shared state and clear authority boundaries between OT and enterprise systems.
The principal failure mode is production-grade AI trapped in local pilots because the operating architecture cannot propagate decisions across sites or supply networks.