AI exposure: Electrical Engineers

30.9% of this occupation's weighted task load is exposed, which puts Electrical Engineers at the 54th percentile of 923 occupations. The capability is largely there. Its average task scores 2.1 out of 4 on what a current system can produce, and the frictions that hold other jobs in place are comparatively weak here.

What holds the line here is verification cost. Across this occupation's 22 tasks it averages 2.01 out of 3, the highest of the five friction dimensions. In plain terms, checking the output costs more than producing it. Where an undetected error is expensive, dangerous or irreversible, the economics change. Someone has to verify the work, and verifying can cost as much as doing it. This is the friction most likely to fall as tools for checking improve.

The most exposed thing this job does is Compile data and write reports regarding existing or potential electrical engineering studies..., at 73.3%. The least is Conduct field surveys or study maps, graphs, diagrams, or other data to identify and correct..., at 0.0%. A gap of 73.3% 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 47 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 22 tasks, 9 are currently banded exposed, 7 assisted and 6 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.