Nobody in the offshore energy industry would say they are not thinking about AI. The conversations are happening. The procurement decisions are being made. The platforms are being upgraded.
The problem is that the workforce has not kept pace. Not because people are resistant or because the technology is too complex. Because the training infrastructure has not caught up with the software. And in most offshore operations, that gap is invisible until it causes a problem.
Here is what that looks like in practice. A survey company upgrades to the latest version of Qimera. The software now has integrated machine learning tools for seabed classification and automated bottom detection refinement. The existing team is certified on Qimera. Nobody is trained on the machine learning module. So the team runs the software the way they always have, ignoring features that, used correctly, would cut processing time significantly and improve classification accuracy. The upgrade investment delivers maybe sixty percent of its value.
This pattern repeats across disciplines. DP systems with predictive AI for station-keeping. Inspection workflows with AI-assisted image analysis. Remote operations platforms that assume operators understand what the system is doing autonomously and what it requires a human decision on. The tools have changed. The training has not.
