Research Finds Generative AI Leads to More Work, Not Less

Generative AI is often presented as a way to ease the strain of knowledge work. By lowering the effort needed to draft documents or fix code, these tools appear to free time and mental energy for more deliberate use.

That expectation rarely holds in daily work.

The effort saved on individual tasks does not add up to a lighter overall load. Instead, the ease of using AI changes how people approach their responsibilities and how much they are willing to take on.

As AI becomes part of everyday routines, work expands to fill the available capacity. Tasks move ahead more quickly, responsibilities accumulate without formal discussion, and work slips into moments that once created distance from it.

Even when official hours stay the same, the day feels fuller.

This expansion happens because AI lowers the threshold for accepting more work. Beginning something new feels manageable, and taking on another responsibility feels reasonable.

Over time, these choices build on each other, creating a workload that feels productive while becoming harder to sustain.

Why It Matters: AI reshapes how time is used and how effort is allocated through small, repeated behaviors. Each instance of faster completion or easier initiation influences what feels reasonable to attempt next. Over time, these patterns shape shared expectations about availability and output. When limits are not clearly defined, gains in efficiency raise the amount of work that fits into a day and increase the mental effort required to keep everything moving.

• AI Expands Individual Scope Through Accessibility: Generative tools reduce the need for specialized knowledge at the start of a task. People feel able to attempt work that once required another role or more experience. As a result, individuals begin taking on technical or specialized tasks on their own. Over time, these additions accumulate. Work that might have justified added support becomes absorbed into existing roles. Specialists then carry added responsibility for reviewing, correcting, or guiding AI-assisted work, often through informal channels that are not recognized as part of the workload.

• Ease of Starting Work Reduces Recovery Time: When beginning a task no longer feels demanding, work slips into moments that once created distance from it. Employees prompt AI during meetings or brief pauses between tasks. These actions feel casual and low effort. Over the course of a day or week, they reduce the pauses that allow attention to reset. Work stays present in a low-level way, making disengagement harder even when formal hours have not changed.

• Ongoing AI Activity Increases Attention Demands: AI makes it easier to keep multiple tasks in motion at the same time. Work continues while drafts generate in the background, and previously delayed tasks resurface once AI can handle part of the effort. Each of these open threads still requires human attention for monitoring and judgment, which creates a steady pull on focus. Even though progress feels continuous, the mental cost increases as more work remains active at once.

• Visible Speed Alters Norms Through Observation: When work begins to finish faster, that pace quickly feels normal. Others adjust through observation rather than direction, and expectations recalibrate without being stated. Response times tighten, and higher output becomes assumed. What starts as a benefit turns into a baseline through repetition. Time saved through automation rarely creates space to slow down. It is absorbed by additional tasks that feel acceptable in the moment.

• Sustained Intensity Weakens Long-Term Performance: The early phase of AI adoption often feels energizing, with experimentation bringing a sense of momentum and progress. Over time, however, the added workload begins to weigh on attention and judgment, making it harder to step away from work. Because much of this extra effort is self-directed, it often goes unnoticed until mistakes increase or engagement starts to fade. The research highlights the importance of clear norms around pacing, stopping, and maintaining human connection so work remains sustainable over time.

Go Deeper -> AI Doesn’t Reduce Work—It Intensifies It – Harvard Business Review