AI exposure: Wind Energy Engineers

Wind Energy Engineers is one of the unusual cases where capability and friction are both high. Current systems can produce a great deal of this work, with average capability across its tasks at 2.2 out of 4. Only 31.2% of the weighted task load comes out as exposed, because 24.8% of it runs into something structural. Jobs in this band tend not to disappear. They change shape, and the person stays.

What holds the line here is context. Across this occupation's 16 tasks it averages 2.12 out of 3, the highest of the five friction dimensions. In plain terms, the work depends on knowledge the model cannot hold. Much of this job runs on things that were never written down: what this particular organisation does, what happened last week, what the person across the table actually meant. That context is the barrier, and it erodes as systems are given more access.

The most exposed thing this job does is Write reports to document wind farm collector system test results, at 73.3%. The least is Direct balance of plant (BOP) construction, generator installation, testing, commissioning, or..., at 3.3%. A gap of 70.0% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.

Within architecture and engineering occupations, this one is less exposed than the median of 37.5% across the group's 56 roles, with 45 scoring higher. Being in an exposed family does not make a particular job exposed, and the reverse holds too.

What would move this score. Of 16 tasks, 9 are currently banded exposed, 3 assisted and 4 untouched. For that distribution to shift materially would take a change in who is permitted to sign the work, which is a question for regulators rather than for engineers. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.