Technical consultancy carries a professional signature at the end of the report, and that changes what AI can safely do in it. Leapfrog Geo and Micromine will build an implicit model far faster than manual interpretation, and acQuire will manage the data behind it — but a Competent Person is signing the resource estimate, and a code-compliant report has to survive peer review.
The dependency is documented interpretation workflow. Where modelling decisions live in the modeller's head rather than in a written methodology, two geologists produce two models from the same drillholes and neither can be defended as a firm-wide standard. Automation makes that faster without making it more defensible.
People carries unusual weight here, second only to Process. Technical judgement is the product, and where it is concentrated in a handful of individuals, AI amplifies whatever their undocumented approach happens to be.
This assessment asks about your interpretation workflows, your validation and your peer review, then tells you which technical AI tools can work on that basis and which need the methodology written down first.
Every industry is scored against its own targets. Process carries the most weight here, so a gap there costs more than the same gap would elsewhere.
Your report says which of these to buy now, which to wait on, and which are held back by something you have not fixed yet — and which of the ones you already pay for are underperforming.
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