A 2026 psychology study found that unfair or pointless job tasks increase quiet quitting by draining workers’ psychological resources, but AI assistance may reduce the risk

In a 2026 study titled ‘Illegitimate tasks and quiet quitting: a moderated mediation model based on the strength model of self-control’ published in Frontiers in Psychology, Liu, Chi, and Sui found that being given unfair or pointless work at the office drains workers’ psychological energy, and that drain directly feeds quiet quitting. The researchers also found a partial buffer: employees who use AI tools display a weaker form of that effect.

The study, which surveyed 229 full-time employees in three waves, two weeks apart, offers a task-level explanation for a phenomenon affecting the American workplace

Why quiet quitting matters in the US
Before we dive into what the study found, it helps to understand the scale of the problem it addresses. According to Gallup's State of the Global Workplace 2024 report, 50% of US workers were not engaged at work in 2023, which aligns with Gallup's own definition of quiet quitting. This report claims that disengaged employees are responsible for the $1.9 trillion loss in productivity in the US alone. Not only does the Liu et al. study tell us what quiet quitting might look like, but it also tells us how it happens, step by step.


What the study identified as the trigger: "illegitimate tasks"
The research is built around a particular concept: illegitimate tasks. According to this study, these are work demands that violate what employees reasonably expect from their role, tasks that seem unnecessary or unreasonable.

Imagine a software engineer buried in admin paperwork, or a designer doing somebody else’s expense reports. According to this study, these are not just frustrating; they may contribute to ego depletion, which can precede quiet quitting.

The mechanism the researchers uncovered: ego depletion
The study is based on the strength model of self-control, a well-established model in psychology. The basic idea is that self-regulation draws on a finite pool of mental resources. Every time you suppress a frustration, handle a feeling you didn’t ask for, or give in to a demand that seems to you unfair, you are probably taking from that pool.

According to Baumeister and Vohs’s research, ‘Self-Regulation, Ego Depletion, and Motivation,’ published in Social and Personality Psychology Compass, on whose foundational work the study builds, when that pool runs low, a state called ego depletion, people become far less capable of sustaining effortful, self-directed behavior. The simplest way out at work is quiet quitting: do the bare minimum, hoard whatever energy you have left, and give nothing beyond what is necessary.

According to this study, the three-wave data supported this chain. Those who reported more illegitimate tasks had significantly higher ego depletion two weeks later. Higher ego depletion predicted significantly more quiet quitting two weeks later. Ego depletion fully mediated the relationship; once it was accounted for, the direct effect of illegitimate tasks on quiet quitting became non-significant. The drain was the mechanism.

What the study found about AI
The researchers also investigated whether employees' use of AI could reduce this process, specifically the extent to which they use AI tools to perform information-heavy, repetitive, or procedural tasks in their work.

According to this study, employees who used AI tools more showed a somewhat weaker link between illegitimate tasks and ego depletion, though the researchers describe this moderation as modest. The idea is that if AI takes some of the tedious parts of an unreasonable task, the employee could spend less mental energy getting through it. Less energy expended equals less depletion, and less quiet quitting downstream.

But the researchers are careful to note the limitations. The study found that illegitimate tasks remained a significant predictor of ego depletion even among high AI users, and the formal moderated mediation index was marginal rather than conventionally significant. AI mutes the effect. It does not eliminate the source.

What the findings mean for American workers and managers
In the US, the implications of the study could be particularly resonant, where researchers and workforce analysts have noted a cultural expectation to go above and beyond as the baseline, though how widely that norm holds varies across industries and roles. A 2025 literature review in the International Journal of Innovative Science and Research Technology by Basha and Pathania found that quiet quitting is a process that unfolds over time in response to multiple workplace stressors. According to this review, the connection between burnout and quiet quitting is strong, citing an industry survey suggesting that the majority of quiet quitters report feeling burned out. And that is not a lack of ambition. That is a depleted person doing the only thing they have the energy left to do.

Liu et al.’ s study suggests that individual tasks that seem pointless or are allocated poorly may erode the psychological resources people need to remain engaged.

For managers, this could mean the quiet-quitting conversation should change. When disengaged workers are regularly given role-violating assignments, telling them to work harder misses the point. The right question is whether employees are consistently taking on work that falls outside their roles or lacks clear justification. When they are, disengagement is not a character flaw, but probably the predictable result of a system that has demanded too much from people’s finite psychological resources.