AI tools don't lead to more leisure time; they intensify work by providing massive leverage. Users can execute ideas more easily and tackle more ambitious projects. The net result is an increase in output and project scope, allowing individuals to accomplish more in a day, often with less fatigue because tedious tasks are automated.

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.

A Berkeley Haas study finds AI doesn't reduce work but intensifies it through 'task expansion.' Professionals use AI to venture into adjacent roles—like product managers writing code—widening their job scope and increasing total output, rather than simply doing their old job faster.

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.

The shift to powerful AI agents creates a new psychological burden. Professionals feel constant pressure to keep their agents running, transforming any downtime—like meetings or breaks—into a source of guilt over 'wasted' productivity and underutilized AI assistants.

Engaging with AI is a high-intensity mental workout, shifting the nature of work to 'cognitive synthesis.' Users, or 'neural athletes,' must constantly adjudicate between what the model says, what they know, and organizational needs, creating a new and profound cognitive strain.

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.

The primary source of employee burnout in the AI transition isn't just an increased workload. It's the friction created when a small group of highly-skilled AI adopters dramatically outpaces their colleagues, leading to resentment and an unsustainable workload for the high-performers.

Employees produce low-quality AI work not because they are lazy, but as a symptom of a leadership problem. The combination of generalized mandates to use AI and increased workload expectations creates a perfect storm for 'work slop' as a survival mechanism, rather than a productivity tool.