Why AI Pilots Fail - and How Manufacturers Can Break the Cycle

Why It Matters

Addressing data quality and bridging the IT‑OT divide unlocks AI’s potential to boost efficiency, resilience and sustainability, giving manufacturers a competitive edge in a rapidly digitising industry.

Summary

AI pilots in manufacturing stall—up to 90% fail—largely due to fragmented, low‑quality data and entrenched IT‑OT silos rather than algorithmic flaws. Experts argue that scaling AI requires a unified, trustworthy data infrastructure that can ingest and analyze industrial data at scale, turning unstructured information into actionable insights. Integrated IT‑OT teams must collaborate to embed AI into production, supply‑chain and maintenance processes, with cross‑functional ownership and ROI‑focused metrics. Shifting from isolated pilots to a resilient, data‑driven operating model is essential for delivering measurable gains in throughput, energy use, yield and downtime reduction.