Putting AI to work for manufacturing How to turn intelligence into operational impact AI is everywhere. Scalable value isn’t. Manufacturers aren’t short on AI. Organizations are investing in capabilities that predict failures, surface risk, and generate insight at scale. In many cases, AI is doing exactly what it was designed to do. But insight alone doesn’t create value. The challenge lies in what happens – or doesn’t happen – next. Across manufacturing, a similar pattern is playing out. A manufacturer invests in predictive maintenance, a supply chain visibility tool, or agentic AI to support service teams. The model works, the signals are accurate, and the recommendations are useful. But further down the line, the outcome still falls short. AI highlights what needs to happen. But it can’t, on its own, ensure the work gets done. A maintenance alert still needs someone to interpret it, raise a ticket, check asset history, find the right technician, and source available parts