AI Governance Framework - Manufacturing Edition

Overview

Manufacturing AI touches the physical world. Robots can injure workers. Quality AI can miss defects in safety-critical parts. Predictive maintenance failures can cause equipment damage. The stakes in manufacturing AI governance are fundamentally different from digital-only AI.

This framework provides governance designed for industrial environments. It prioritizes safety while enabling AI benefits and addresses the unique challenges of OT integration, supply chain complexity, and quality requirements.

What's Inside

• Why Manufacturing AI Governance Is Different: Safety-critical nature, OT environment challenges, supply chain complexity, quality certification requirements, worker impact considerations
• Regulatory Landscape: OSHA requirements, EU Machinery Regulation, ISO quality standards (9001, IATF 16949, AS9100), machine safety standards, emerging AI regulations for industrial applications
• Framework Architecture: Manufacturing-adapted governance structure
• The 5 Pillars for Industrial AI:
  • Strategy & Leadership for manufacturing objectives (productivity, quality, safety)
  • Risk Management emphasizing safety and operational continuity
  • Compliance with industry standards and certifications
  • Ethics prioritizing worker safety and fair treatment
  • Operations for OT integration and factory floor reality
• Organizational Structure: Manufacturing-appropriate roles bridging IT, OT, quality, and safety
• Implementation Roadmap: Phased approach accounting for production schedules and capital cycles
• Use Case Governance: Specific governance for predictive maintenance, quality inspection, robotics, production optimization, supply chain AI
• Safety-Critical AI Governance: Enhanced governance protocols for AI affecting worker safety, protocols for human-robot collaboration, emergency override procedures
• Governance Maturity Model: Manufacturing-specific maturity levels
• Case Studies: Industrial AI governance examples

Who This Is For

• Chief AI Officers in manufacturing companies
• Manufacturing CIOs/CTOs integrating AI into operations
• Quality Directors maintaining certifications with AI
• Plant Managers deploying AI on factory floors
• Safety Officers ensuring AI doesn't compromise worker safety

Why This Resource

Manufacturing governance must bridge IT and OT cultures, integrate with existing quality and safety systems, and address physical-world consequences. This framework understands manufacturing realities—quality audits, safety protocols, production schedules, and union considerations.

Safety-critical governance sections provide enhanced protocols for high-risk industrial AI applications.

FAQ

Q: How do we govern AI that affects worker safety?

A: The safety-critical AI governance section provides enhanced protocols: safety impact assessment, human oversight requirements, emergency override procedures, and integration with existing safety management systems.

Q: What about maintaining ISO certification with AI?

A: The compliance pillar addresses ISO and industry certification requirements—how to document AI validation, maintain process control, and satisfy auditor expectations while using AI in certified processes.

Q: How do we integrate AI governance with OT security?

A: The framework addresses OT integration throughout, including security considerations, network segmentation, and governance for AI at the IT/OT boundary.