When operational IoT meets software strategy
AI investment now reaches into power, cooling, packaging, logistics, and automation, because compute capacity relies on systems that keep hardware operating. The constraints affecting data centre build-outs therefore also affect distributed infrastructure, factory systems, labs, warehouses, and field operations – where edge and IoT teams have to connect equipment, gather data, maintain uptime, and support process control.
Cloud companies are increasing capital expenditure for data centres, while semiconductor sales and demand for AI systems continue to rise. McKinsey’s estimate of the potential contribution of generative AI to the economy gives one measure of scale, but the more relevant point is that AI capacity is limited by physical systems. Data centres require power and cooling, chip production requires packaging capacity, process control, inspection, and material handling. Manufacturing sites require equipment integration, records, alarms, and maintenance. These requirements belong to operations and are an integral part of any technology strategy.
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