In the past there was an implicit contract for white-collar employment that was based on the concept of earned experience through a period of manufacturing type work. You enter your profession by performing uninteresting, low-paying manufacturing tasks (such as, writing boilerplate type code or performing low-level quality assurance) while you gain domain expertise and gain the perspective necessary to perform high-value work at a higher level.

LLMs are now exceptionally good at consuming the 20% of an employees entry-level responsibilities.

What I see happening in the enterprise is that management is using AI to justify pulling the ladder up behind them and closing the door behind them. When a senior engineer's or senior analyst's productivity has increased by 30% due to using LLMs, the executive's response is typically not great, we have more time to work on bigger projects, but instead great, we can freeze junior hiring for 2 years.

The entry-level positions in the labor force are being automated, causing seriously low access to those roles for the Gen Z workforce. On the other hand, most senior-level positions are not being available to Gen Z workers as they lack the skills and experience required to qualify for those positions.

Stagnation in the adoption of artificial intelligence (AI) technology is the direct result of having no entry or junior level employees to work underneath senior staff members, causing a bottleneck for seniors. Employees generating raw output with AI technology have to check the results (output) for accuracy before integrating into work systems and processes as there are no entry-level employees to provide assistance to senior workers.

Gen Z workers do not dislike the tool (AI) however, they do not like how the tool is being implemented and used currently. Currently, the implementation of AI is driven by cost cutting in terms of labor rather than being focused on providing training and developing Gen Z's human capital for future use.

Sue me, I have that right.

Interesting results regardless when they compare the shift of 2025 to 2026

I love the cognitive dissonance.

Even in the best case scenario where the generated wealth will be distributed, and somehow we will be able to keep them in check (unlikely), what would be the point of life in a world where machines can best us at everything?

The main social problem with automation in general was that less intelligent people have been left behind as only boring physical tasks are left for them to do, and people don't generally want to go back destroying their body from the prospects of an office job.

At some point frontier AI will only getting only worthwile to use for only super highly intelligent and motivated AI researchers which is a tiny part of the population.

I guess cynicism is trendy.

Sell NVIDIA!!!

31% seems remarkably high. Here we seem to be running up against the limitations of statistics. It is hard to interpret whether this is a scared-and-angry sort of angry or if there is something AI-related happening that is making them angry. I might have been lucky in my experiences, but generally if people get angry there is a reason other than "things are changing".