The 2023 skill erosion argument was easier to dismiss as an old automation story. In 2026 it is harder to dismiss.
The point is not that AI makes people stupid. The point is that AI makes it very easy to skip the part where competence is actually formed.
Seniors can use AI as leverage because they already know what a good result should look like. They can see what is wrong or missing, where it is going to break first, where it violates the domain, or where it creates future maintenance cost.
A junior, or a weak team, may use AI to jump directly to output. And output is dangerous here, because it creates the feeling of progress before understanding exists. And all the above places, plus a good 50 others, are where the danger is located.
Skill Offloading
That is skill offloading. Not task offloading. Skill offloading. The work is still done, but the executor no longer builds the ability to do, judge, debug, or recover it.
For software engineering this is exactly the trap. AI can generate code, specs, tests, and explanations. But it cannot replace the engineering judgment behind a vast number of system complexities and evolution demands.
So the real question is not “AI or no AI”. The real question is what exactly we are offloading. Offloading execution can give leverage. Offloading judgment removes the very ability to understand, verify, and own the work.
And that is much more dangerous than bad code. Bad code can be rewritten. Lost engineering judgment is much harder to rebuild, especially when the whole team is losing it at the same time. This is where AI productivity quietly turns into cognitive debt.
Here are the source articles.
2023-2025: Researchers warn that skill erosion caused by AI could have a devastating and lasting impact on businesses - but it may already be too late
2026: When Everyone Uses AI, Companies Risk Critical Skills
