Manufacturers adopting AI for quality control, predictive maintenance and supply-chain optimization face governance questions their existing operational-risk frameworks weren't built for — especially where AI decisions touch safety, warranty exposure or labor relations.
Typical investment: CAD 20,000-100,000 initial engagement, CAD 8,000-25,000/month ongoing
Every sector treats AI governance differently — what counts as a real risk, who signs off on it, and which frameworks actually get referenced in a Board conversation. The breakdown below isn't generic: it reflects how AI governance plays out specifically for organizations in Manufacturing, from the challenges that show up first to the people who typically need to be in the room.
Artificial intelligence management systems — organizational accountability, AI policies, lifecycle governance, risk management and continuous improvement.
The Govern, Map, Measure and Manage approach for identifying and controlling risks arising from AI systems.
Process-based quality-management concepts covering customer focus, leadership, process management and continual improvement.
The stakeholders typically at the table for an engagement in this sector.