Computing cost and reliability remains the bottleneck. AI agents are nowhere near smart enough to carry out tasks on their own. Combined with the fact, 95% of gen-AI pilots "failed" [1], at least failed to improve the bottom line. Layoffs were never about AI, they were almost always about capex, and correcting the pre-2022 overhiring. All CEOs are hearing in 2026, "I didn't get anything done, but the model hit the limit".

However, if there will be, locally deployable, meaningfully capable AI models that can change the computing cost equation.

[1]: https://www.forbes.com/sites/jasonsnyder/2025/08/26/mit-find...