Fears that AI will eliminate entry-level jobs are unfounded due to Jevon's paradox. Just as Excel didn't kill accounting jobs but instead enabled more complex financial analysis, AI will augment the work of junior employees, increasing the sophistication and volume of their output rather than replacing them.

The ease with which AI tools generate ideas and kickstart projects can lead to a productivity paradox. Instead of finishing work, users become overwhelmed with a massive backlog of new, unfinished projects, replacing one bottleneck with another.

Contrary to the narrative of AI reducing work, heavy users find it intensifies their workload. The immense leverage from AI makes it easier to get ideas off the ground and produce more in-depth output. This shifts the productivity gain from "working less" to "achieving more," leading to more complex projects, not more free time.

Research shows that instead of reducing work, AI often increases it through 'task expansion.' Employees use AI to take on work they previously delegated or outsourced, such as a product manager writing code, blurring roles and intensifying their workload.

Counterintuitively, making a task cheaper and easier with AI doesn't just eliminate jobs; it drastically increases the overall demand for that task. Just as Excel created more accountants, AI's efficiencies will lead to an explosion in the volume of work, creating new roles and opportunities.

Productivity gains from AI don't simply reduce the total amount of work. Instead, they unlock new capabilities and analytical depths, creating new types of jobs and expanding what's possible. The long tail of work doesn't get shorter; it gets longer in a different, more complex way, representing a growing pie of innovation.

Productivity models often wrongly assume time saved by AI is redeployed into other work. In reality, many employees use efficiency gains to finish early. This 'human slack' factor dampens macro-level productivity gains, except in highly driven fields like tech, where workers use it to work even more.

Instead of leading to less work, agentic AI tools are causing users to work longer hours. The core reason is psychological: the tools are so effective at generating output that the opportunity cost of not working feels immense. This creates a hybrid of exhilaration and anxiety where time itself is the bottleneck.

A UC Berkeley study found employees using AI worked faster and took on broader tasks, leading to more hours worked, not fewer. AI offloads menial labor, making jobs more purpose-driven and motivating employees to do more, which increases stress and burnout.