Trust Is the Difference Between a Pilot and Production
AI pilots often show promise, but production is where trust is tested. In this focused presentation, Steven FitzGerald of SEEQ explores why many data and AI initiatives stall before they reach daily operations, and why the real barrier is often not the algorithm, but whether people trust the workflow enough to use it.
The presentation makes a clear distinction between AI pilots and production value. Pilots can demonstrate potential through dashboards, proofs of concept and promising models, but production requires shared context, validation, ownership and governance. Without these foundations, even a technically strong AI output can fail if teams cannot understand, verify or act on it with confidence.
A key message is that trust cannot be built without context. Operational data is often fragmented across historians, data lakes, maintenance systems and lab platforms, while much of the critical knowledge still lives with subject matter experts. SEEQ positions experts at the centre of the process, using AI to remove friction, connect data across systems and turn proven ways of working into repeatable, auditable workflows.
The session also highlights what trusted workflows can make possible across upstream, midstream, downstream and LNG operations. From compressor anomaly detection and pipeline monitoring to refinery energy efficiency and offshore well optimisation, the focus is on bringing expertise, context and data together in a way that supports faster analysis, shared understanding and governed action.
The final message is simple: the future is not AI instead of experts, but experts equipped with trusted AI. View the full presentation for a closer look at how Seeq approaches the trust layer needed to move AI from pilot projects into production-ready operating workflows.
