AI in offices, coding environments, and professional workflows increase productivity while also driving stress, multitasking, and leading to an AI burnout as intelligent technologies reshape how work is done, according to a Harvard Business Review study based on employee experiences.
AI tools can accelerate tasks and reduce manual effort, but their use often intensifies the human workload rather than easing it.
Then, employees become trapped in cycles of constant task-switching, more expectations leading to mounting pressure, raising urgent questions about how companies adopt and regulate AI burnout responsibly.
AI-Generated ‘Workslop’ Is Widespread and Problematic for Many US Employees
For some software engineers, such intelligent technologies feel like both a blessing and a curse that’s birthing a state of AI fatigue. Siddhant Khare, a US based programmer, told Business Insider that AI has made him more productive, yet his job has never felt harder.
“We used to call it an engineer, now it is like a reviewer,” Khare said, adding that “every time it feels like you are a judge at an assembly line and that assembly line is never-ending, you just keep stamping those [pull requests].”
In his essay, “AI fatigue Is Real,” Khare described the cost, highlighting that he “shipped more code last quarter than any quarter in my career. I also felt more drained than any quarter in my career.”
Researchers in the Harvard Business Review observed a similar dynamic after monitoring 200 employees over eight months, finding that the AI workload acceleration of “certain tasks […] raised expectations for speed; higher speed made workers more reliant on AI. Increased reliance widened the scope of what workers attempted, and a wider scope further expanded the quantity and density of work.”
The unintended result is a form of “workload creep,” where employees voluntarily take on more than they can sustainably handle. Multitasking spikes, deep focus declines, and the very skills AI is meant to augment can atrophy.
Khare compared it to GPS overreliance, “Before GPS, you built mental maps. You knew your city. You could reason about routes. After years of GPS, you can’t navigate without it. The skill atrophied because you stopped using it.”
This growing reliance contributes to AI and cognitive fatigue, which can reduce both creativity and decision-making capacity.
Guardrails and Human Limits
AI, in other words, doesn’t burn out people do. Even in companies where AI adoption is voluntary, enthusiasm for technology quickly morphs into constant pressure, eroding focus and well-being. Khare believes there are ways to use AI sustainably, but he warns that both employees and developers must share responsibility.
“You need to keep some sort of guardrails for the humans, so they don’t self-destruct themselves,” Khare told Business Insider.
Failure to do so can amplify AI burnout symptoms, manifesting stress, irritability, and declining productivity. The study also teaches us an important lesson, which is that unless proper policies and measures are in place, AI burnout may exacerbate human errors and pressure rather than relieving them.
Organizations looking to incorporate AI need to establish codes of practice, monitor work rates, and cognitive ability in addition to productivity rates. Without careful management, the combination of AI increased workload and constant task-switching may contribute to chronic AI and cognitive fatigue.
This cycle of dependency highlights the need for careful AI workload orchestration and limits, otherwise the revolution in the workplace that AI is supposed to bring may actually result in an epidemic of AI burnout.
For many, the symptoms of AI burnout symptoms range from mental exhaustion to emotional detachment to mirror those of traditional workplace stress, only magnified by technology.
Over time, unchecked AI and cognitive fatigue can impair judgment, slow learning, and diminish the very skills AI is intended to enhance, creating a paradox where automation increases human strain.
Ultimately, awareness, monitoring, and sustainable practices are key to preventing AI burnout, ensuring AI becomes a tool for empowerment rather than a driver of human collapse.
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