Artificial intelligence is reshaping advanced manufacturing, especially processes involving ceramics, glasses, and other hard or brittle materials. But adopting AI is far more difficult than simply buying software and connecting machines. Manufacturers must understand the advantages and limitations of different models, so they can determine where AI fits best within their operations.

Manufacturers who do not critically plan out AI adoption often end up with promising pilots that never scale. A better approach is to treat AI as a long-term capability built on four pillars: data and infrastructure, disciplined use cases, scaling awareness, and people.