As AI use explodes in asset-intensive operations, reliability, integrity and maintenance leaders face two critical challenges: learning how to build and test the right AI tools and knowing when AI is genuinely the best solution. Through comparative examples drawn from actual maintenance, inspection and turnaround environments, attendees will learn how to develop an AI toolbox, validate models safely, and apply clear criteria for deciding when AI adds value and when simpler automation delivers better outcomes with less complexity.
● Assessing AI readiness: Ensuring people, systems and assets are AI‑ready, from OT compatibility to upskilling frontline maintenance teams
● Developing an AI roadmap with clear success metrics, business value alignment and real-world examples of what "success" looks like
● Building and testing AI models safely through structured POC environments
● Identifying essential data requirements for PdM, CBM, RBI, inspection analytics and turnaround optimization
● Identifying use cases: Determining when AI is the right tool VS when simpler automation can achieve the same
reliability outcome more efficiently
● Implementing governance and oversight frameworks that maintain traceability, control and auditability