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.

The common fear of AI eliminating jobs is misguided. In practice, AI automates specific, often administrative, tasks within a role. This allows human workers to offload minutiae and focus on uniquely human skills like relationship building and strategic thinking, ultimately increasing their leverage and value.

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.

The work of managing AI agents isn't less, it's different. It trades the emotional exhaustion of managing people for a more intense, sustained cognitive load, as you're constantly problem-solving and optimizing systems rather than dealing with interpersonal issues.

In the digital age, traditional metrics like hours are obsolete for knowledge workers. Productivity is a holistic equation including rest and recovery. As AI handles repetitive tasks, human effectiveness—fueled by well-being—becomes the key differentiator and a core driver of business value.

When AI empowers non-specialists to perform complex tasks (e.g., marketers writing code), it creates a new, hidden workload for experts. These specialists must then spend significant time reviewing, correcting, and guiding the AI-assisted work from their colleagues, creating a new form of operational drag.

Developers using AI agents report unprecedented productivity but also a decline in job satisfaction. The creative act of writing code is replaced by the tedious task of reviewing vast amounts of AI-generated output, shifting their role to feel more like a middle manager of code.

The capability for AI agents to work asynchronously creates a novel form of professional anxiety. Knowledge workers now feel a persistent pressure to have agents productively building in the background at all times, leading to a fear of falling behind if they aren't constantly orchestrating AI tasks.

Using AI tools to spin up multiple sub-agents for parallel task execution forces a shift from linear to multi-threaded thinking. This new workflow can feel like 'ADD on steroids,' rewarding rapid delegation over deep, focused work, and fundamentally changing how users manage cognitive load and projects.