AI for Reliability at Domtar: Hype, Help, or Hard Truths?

The question of which technologies truly advance reliability performance remains a central and ongoing discussion at Domtar. As digitalization accelerates, Artificial Intelligence (AI) and machine learning have emerged as highly promising—but often misunderstood—tools in the reliability space. While the potential is significant, translating that potential into measurable results in complex industrial environments is far from straightforward.

At Domtar, the corporate reliability group is actively researching, piloting, and evaluating a range of technologies, from advanced analytics platforms to AI-driven condition monitoring solutions. Through this work, it has become clear that the challenge is not simply selecting the right tools, but understanding how to integrate them effectively into existing reliability practices and organizational behaviors.

This presentation will explore three critical gaps that must be addressed to realize the full value of AI and related technologies:

• The Tools vs. Basics Gap– the disconnect between investing in advanced technologies and maintaining strong foundational reliability practices
• The Know vs. Do Gap– the difference between understanding best practices and consistently executing them in daily operations
• The “What You Buy vs. What You Get” Gap– the misalignment between vendor promises and actual, realized performance in the field

Drawing on real-world experiences from Domtar’s operations, this session will provide practical insights, lessons learned, and a grounded perspective on how organizations can bridge these gaps to move from technology hype to sustainable reliability improvement.