More and more employees are fed up with AI. Several current studies show that instead of the productivity gains that are often promised, many people experience mental exhaustion, declining motivation and creative blockages. Researchers also call this phenomenon brain fry. A commentary analysis.
AI fatigue is affecting more and more employees
- More and more employees are longing for a time without AI. This is the result of a survey by the technology consulting company Adaptavist. Accordingly, 41 percent of so-called knowledge workers in Germany would prefer to work without artificial intelligence. One of the main reasons (45 percent): The Dealing with low-quality AI contentwhich makes tasks seem less meaningful and more repetitive. 37 percent of those surveyed feel less motivated as a result. Another 25 percent said that AI models would limit their creativity.
- A study by the Boston Consulting Group comes to similar results. People who use or monitor AI systems intensively suffer significantly higher mental fatiguea phenomenon that researchers also call “brain fry.” In this context, respondents described a feeling of mental confusion. This in turn is accompanied by difficulty concentrating, slower decision-making and headaches. For companies, such a development can bring exactly the opposite of the expected productivity gain. The reason: misjudgments and excessive expectations.
- Fewer and fewer people in Germany believe that technology can solve humanity’s central problems. Among them: poverty, hunger and climate change. This is one of the results of the TechnikRadar 2026. The use of AI in particular is viewed critically. Around 85 percent are bothered when AI makes decisions for them. According to a survey by the digital association Bitkom, around three quarters of users enjoy using artificial intelligence. But more than 40 percent of Germans would would rather live in a world without AI. The background: a mixture of skepticism, uncertainty and general rejection.
The problem is not AI, but how to deal with it
AI fatigue is not a sudden phenomenon. She is that Result of false expectations and an AI hype in which there is hardly any room for nuances between promises of salvation and doomsday scenarios. The problem: AI is not a messiah, but a tool. And this needs to be used sensibly and specifically so that it is effective.
That means: The problem with AI fatigue is not necessarily the technology itself, but often inflationary and thoughtless handling with her. Artificial intelligence can help, above all, to evaluate enormous amounts of data and take on repetitive tasks. However, it also produces more and more content that needs to be checked, sorted out or corrected.
In other words: from a supposed time saving can quickly even become an additional expense. Anyone who spends half their working day checking AI results or switching between countless tools and browser tabs is not working more efficiently, but simply more hectic. This can be nerve-wracking in the long run and lead to mistakes. The victims are often creativity and concentration.
There is also a reflex that can currently be observed in many companies: the main thing is AI. But not every process gets better just because a language model runs over it. The media hype has created the expectation in many places that all software suddenly needs AI. Less would often be more. Anyone who involves employees, critically questions processes and stands up few really useful tools focused, is likely to be more successful in the long term than those who chase every new AI trend.
Voices
- Lisa Schaffer, Global Work Management Practice Lead at Adaptavistin a statement: “We expect people to become faster, work smarter and embrace AI, while at the same time more and more of them are quietly wondering whether there is a place for them in the future. This tension doesn’t just go away on its own. It’s reflected in their employee retention metrics, engagement and their corporate culture. But here’s the opportunity: companies that take these fears seriously and invest in their people alongside technology will emerge as winners from this transformation. AI doesn’t have to mean uncertainty. It can mean growth – if we Actively shape the path there.”
- Ralf Wintergerst, President of the digital association Bitkomsuggests a different approach to AI: “Artificial intelligence has enormous disruptive potential and is changing our everyday life and our working world at a pace that understandably unsettles many people. The best antidote to uncertainty is knowledge. We need comprehensive offers that give people of all ages easy access to AI, from primary school to vocational school and the workplace to adult education centers for senior citizens. A digital gap must not even arise between people with and without AI.”
- Josephine Hofmann, who researches at the Fraunhofer Institute for Industrial Engineering and Organizationknows the AI hangover phenomenon. She told Impulse magazine: “The question is: Are we really more productive? Or does AI produce much more information than we actually need? (…) When it comes to artificial intelligence, companies are currently trying out an incredible number of things. In some cases there is a lack of a clear system, which can overwhelm employees.” AI expert Jens Polomski strikes a similar note: “Several AI tools in parallel force the brain to constantly multitask. At the same time, the expectations placed on employees are increasing. Managers say: Now we have AI. Why don’t you work faster? That’s crazy.”
What needs to change
It shouldn’t always be about what AI can theoretically do. What is more important is what it can do well and, above all, what makes sense. There is often a bigger gap than that between technical feasibility and practical use Promise of salvation from AI providers suggest. But the greatest progress does not occur where as much as possible is automated, but rather where people are noticeably relieved.
Anyone who simply tells employees that they just have to get used to AI will encounter resistance. Because acceptance does not come from announcements, but from understanding. Employees must be given the opportunity to assess opportunities and risks themselves and to critically question their use.
Otherwise there is a risk of one Endless loop of optimization pressure; with more and more tools, more and more expectations and less and less time for the actual work. Or: AI should primarily take on recurring tasks that are unnecessarily burdensome – and not constantly create new ones.
In the end, success will not be measured by whether AI is used, but how. This requires clear rules Put people at the center – and not just business interests or the fascination for what is technically possible.
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