Direct answer
Enterprise AI is built for documents, email, and office workflows. Industrial AI is built for the plant floor: it integrates with operational systems like SCADA, MES, and ERP, respects the separation between operational technology (OT) and IT, and is measured on operational KPIs rather than demo impressions.
The differences that matter
| Dimension | Enterprise AI | Industrial AI |
|---|---|---|
| Data sources | Documents, email, CRM, tickets | SCADA, MES, ERP, historians, equipment manuals |
| Safety model | Standard IT security | OT/IT separation — never in the line's control path |
| Success metric | Productivity, deflection | Uptime, scrap, energy, time-to-answer |
| Users | Knowledge workers | Operators, maintenance, plant leadership |
| Failure cost | A bad draft | A stopped line or a safety event |
Why the distinction is practical, not academic
A generic enterprise chatbot bolted onto a factory fails because it can't reach plant data, can't honor the safety boundary, and isn't judged on the metrics the plant actually cares about. Industrial AI is designed around those three constraints from day one — which is why it ships to the floor and stays there.
See how we apply this on the Industrial AI page, including the MillMind reference deployment.