The de-weirding impulse produces a second, deeper failure: it leads companies to default towards automation rather than augmentation. When leaders see studies showing productivity gains of 30% from AI, their instinct is to cut 30% of the workforce. That arithmetic is simple. What is hard, and requires genuine imagination, is asking a different question: what does it mean to rebuild an organisation around the fact that a single programmer can now write a hundred times more code? What new products become possible? What new markets open up? No vendor can answer those questions for you. No consultant has a playbook (much as they might claim they do). The hard strategic work of reimagining what your organisation could become is precisely the work that de-weirding AI allows companies to avoid.
And, an interesting framing of shadow IT:
There is one more problem that de-weirding creates, and it may be the most consequential. When companies fail to create the right incentives, employees respond rationally: they hide their AI use. Some fear punishment. Some do not trust that productivity gains will be shared with them rather than captured by the firm. Some quietly work 90% less and see no reason to volunteer that information. The result is an enormous information gap. Managers cannot see the true impact AI is already having inside their own organisations, which makes it even harder to develop a real strategy.