Scaling Industrial AI from Pilots to Value: Target Architecture
by
SPREAD Team
on
Scaling Industrial AI from Pilots to Value: Target Architecture
Many AI initiatives in engineering start with promising pilots but struggle to scale into production environments.
The Scaling Industrial AI from Pilots to Value whitepaper outlines a practical reference architecture for applying AI across the product lifecycle in manufacturing. The document focuses on how organizations can connect existing engineering systems, structure product data, and deploy domain-specific workflows that make AI usable in daily operations.
The architecture spans R&D, production, and aftersales, and addresses common barriers such as siloed engineering data, fragmented tool landscapes, and AI projects that never move beyond prototypes. 
THE PAPER DESCRIBES THE ARCHITECTURE REQUIRED TO SCALE INDUSTRIAL AI:
- Build a layered AI architecture spanning infrastructure, data, ontology, and execution workflows
- Connect existing engineering systems instead of replacing them, enabling AI adoption without large IT transformations
- Turn AI pilots into reliable cross-system workflows by using semantic layers and enterprise knowledge graphs to create context across product data