Your Plant Has the Data. Your AI Cannot Reach It. Here Is Why That Is the Core Problem in Chemical Manufacturing. Every major chemical company is running AI projects. Most of them are quietly struggling. The issue rarely sits with the models. It sits with the data infrastructure underneath them – which was never designed for this purpose. Ask any chemical engineer what is holding back digital transformation at their site and the answer is rarely a shortage of ambition or budget. It is infrastructure. Specifically, the persistent gap between operational technology (the PLCs, distributed control systems, SCADA platforms and process historians that run the plant) and information technology, the enterprise systems, cloud platforms and analytics tools where AI models are built and deployed. These two domains grew up separately, governed by different engineering disciplines with different priorities. OT was designed above all for reliability and uptime. An instrument that ...
