Whose Time is Saved by AI? Reasons People Leave a "More Convenient Workplace"

AI summarizes materials, writes programs, and prepares for analysis. If working hours are shortened, employees should have more leeway.

However, faster work does not necessarily mean employees will want to continue working at that workplace.

A survey targeting professionals in Germany revealed cases where colleagues left the company due to AI-related reasons. The underlying issues are not just simple "fear of AI." They include significant changes in job content, lack of growth prospects, and increased workload.

In Japan, when incorporating AI into business operations, it is necessary to focus on the subsequent work style as much as the performance of the tools introduced.

"38.4% Resignation" Is Not the Whole Story—What the Numbers Indicate

According to an article by dpa-AFX published on October 24, 2026, by Aktiencheck, YouGov, commissioned by the human resources consulting firm SThree, surveyed 817 employees in Germany's MINT fields during the summer.

MINT is a German acronym referring to mathematics, information science, natural sciences, and technology fields. It is a concept similar to STEM used in English, including professionals such as engineers, IT personnel, and research and development.

In the survey, 38.4% reported that colleagues in their team left the company for AI-related reasons in the past 12 months.

This needs to be read carefully.It is not the result that "38.4% of professionals resigned due to AI." It is merely the percentage of respondents who reported colleagues' resignations. Multiple colleagues may have responded about the same resignant, and this number cannot be used to calculate the number of resignations or the overall turnover rate of the company.

Moreover, it differs from results directly surveying the resignants themselves. Whether AI was the sole cause or if it overlapped with pre-existing dissatisfaction cannot be determined from the information in this article alone.

Nevertheless, it conveys that workplace changes accompanying AI have become an unavoidable issue when considering employee retention.

It's Not Just the Fear of Losing Jobs: The Issue of "Changes in Job Content"

Among the reasons for resignation indicated in the article, 52.2% of applicable respondents cited that their job content "changed beyond recognition." A lack of growth and career development prospects was cited by 46.5%, and unbearable workload by 36.9%.

These are not percentages of the entire survey respondents but the figures shown in the article as reasons for resignation. It is also important not to reinterpret them as responses from the resignants themselves.

What exactly does the change in job content entail?

For example, someone who used to construct texts or design proposals might shift to a role where they check AI outputs, look for errors, and give correction instructions. While this is not a specific case confirmed by the survey, it serves as an example to understand changes in work.

Even if the goal of completing deliverables remains the same, the daily experience feels different.

For those who found fulfillment in thinking and shaping things themselves, focusing on checking and supervising might make them feel distanced from their preferred work. On the other hand, some may rejoice in being freed from simple tasks and being able to focus on more advanced judgments.

This is why a single indicator of "work speed has increased" cannot measure the satisfaction with job content.

Reports of Resignations Noted in the Life Sciences Field

The percentage of those reporting resignations from teams due to AI-related reasons varied by field.

In life sciences, including biological sciences and medicine, it was 56.8%. In contrast, it was 28.9% in IT and 29.6% in engineering.

However, this difference does not immediately conclude that "AI is taking the most jobs in life sciences." What is being measured is responses regarding colleagues' resignations, not a net reduction in employment.

Furthermore, the article lacks detailed information on the number of respondents by field or the margin of error. Additional investigation into work content, organizational changes, and implementation methods is necessary to understand why the differences arose.

What is noteworthy is that the changes brought by AI are not confined to the inside of IT companies. The more a job uses specialized knowledge, the more important it becomes to specifically explain what roles people will take on after AI implementation.

Productivity Improvement and Resignation Can Occur Simultaneously

Summarizing this survey as "workers dislike AI" would misinterpret the reality.

In Germany, 66.8% of AI users responded that their team's productivity has increased compared to two years ago. As for how they use their time, 38.0% said for strategic thinking, 29.0% for learning and training, and 29.4% for additional tasks.

Positive emotions towards AI, such as "stimulating," "curiosity," and "exciting," outweighed "pressure" and "fear."

In other words, it is quite possible to feel the convenience while being dissatisfied with the way of working.

For example, even if a task takes half the time with AI, if the number of tasks doubles, there is no leeway. The increased speed of output can also lead to more materials to check and cases to judge.

What is questioned here is how to use the time saved by efficiency. Whether to allocate it to learning and improvement or fill it with new tasks. Depending on this allocation, the same AI can become a tool for growth or a factor increasing the burden.

Voices on Social Media Say "Only Deadlines Got Shorter"

Discussions about AI-driven efficiency and work burden can also be seen on social media and online forums.

The following is not a direct response to the current German article but a summary of posts publicly available on related themes. These are anonymous experiences and have not been independently verified, nor do they represent the opinions of all workers.

In the developer community "r/developersIndia" on Reddit, there was a post stating that management now believes "all tasks can be completed in 3-4 hours," and work that previously took weeks is now expected to be delivered in days.

The poster explained that while the next tasks pile up, they are also chased by corrections of previously hastily delivered deliverables. They complain that speed to publication is prioritized, leaving quality checks and worker fatigue behind.

The issue that can be read from this post is not just the performance of AI itself. It is the management approach that considers the shortened task time as the total possible time reduction for all work.

On the other hand, in a related thread on "r/Futurism," a user claiming to have years of development experience commented positively that productivity indeed increases if one grasps the limits of AI.

Even from limited posts, evaluations are not uniform. Separating scenarios where AI is helpful from those where expectations are too high becomes the starting point for discussions.

In Japan, "Post-Generation Work" Is Also Increasing

Regarding Japan, there are relevant figures in the same survey series published by SThree.

In a survey targeting 794 STEM personnel in Japan, 64.9% of the 592 who use AI in their work responded that team productivity has improved compared to two years ago.

On the other hand, 39.4% of all respondents said that the time spent verifying and checking AI-generated deliverables has increased, and 35.4% said the time spent on corrections and adjustments has increased.

This alone cannot definitively say that the overall work burden has increased. A comparison with the time saved in other tasks is necessary. However, merely observing that "generation has become faster" does not capture the actual workload.

Even if a draft of materials is completed in minutes, confirming the basis, aligning with internal circumstances, and adjusting to a quality suitable for clients takes time. If these tasks are not included in the schedule and only deadlines are moved up, there is a risk of concentrating the burden on the person in charge.

Three Things Japanese Companies Should Reconsider

According to the German article, free responses included calls for targeted training, clear rules for AI use, and early employee involvement by management.

Considering these requests in the context of Japanese workplaces, at least three areas need reconsideration.

Firstly,measuring workload from "generation to verification and correction."

The number of times AI is used or the number of materials created alone does not reveal the work's outcome. Only by looking at the time spent on verification, the number of corrections, and issues arising after completion can one understand which processes have become easier and where the burden has shifted.

Secondly,incorporating learning time into work.

While demanding adaptation to new tools, maintaining the traditional workload, and leaving learning to outside work hours, the effort to master AI itself becomes an additional burden. It is necessary to decide not only the content of training but also when it can be learned.

Thirdly,explaining roles and evaluations after AI implementation.

If transitioning from creating work to judgment and verification work, how will that judgment ability be evaluated? Through which tasks will young employees learn the basics, and where will experienced employees demonstrate their expertise?

Simply saying, "We want you to use AI from now on" does not allow workers to envision their future. If job content changes, the path to growth must also be shown.

Consider AI Implementation Outcomes in Terms of "Speed" and "Sustainability"

This survey does not conclude that AI is unilaterally worsening workplaces. Many feel productivity has increased, and many positively accept technological changes.

At the same time, it teaches us that feeling convenience and wanting to stay at a workplace are separate matters.

What will be entrusted after work speeds up? Can part of the saved time be used for learning? Will the increased verification tasks be fairly evaluated? Can one's expertise continue to grow?

When companies verify the outcomes of AI implementation, they should also look for answers to these questions, along with processing numbers and time reduction.

Whether AI expands the potential of workers depends not only on the tool's performance but also on how the surrounding work is designed.

Sources and Reference URLs

1. Aktiencheck/dpa-AFX "Wandel im Berufsalltag: KI wird zum Kündigungsgrund"
   Published on October 24, 2026. Survey on 817 MINT employees in Germany, percentage reporting AI-related resignations, reasons, differences by field, productivity, and emotional data source
   https://www.aktiencheck.de/news/Artikel-Wandel_Berufsalltag_KI_wird_zum_Kuendigungsgrund-20197881

2. SThree "MINT Workforce Report 2026: Built to Adapt"
   Official introduction page by the survey organizer. Overview of an international survey conducted by YouGov targeting 4,126 professionals in the UK, US, Germany, Netherlands, and Japan.
   https://www.sthree.com/de-de/insights/mint-workforce-report/2026/Forschung

3. SThree Corporation "Reviewing Workforce Reduction Accompanying AI Implementation from the Japanese STEM Personnel Survey"
   Announced on October 15, 2026. Official company announcement referencing the number of respondents in Japan, productivity improvement among AI users, and increased time spent on verification and correction of deliverables.
   https://prtimes.jp/main/html/rd/p/000000009.000149028.htmlSThree Corporation Press Release

4. Reddit/r/developersIndia "Sudden increase in workload due to AI causing burnout."
   A post introducing personal experiences regarding shortened deadlines, workload, and the burden of correction work after AI implementation. Referenced as an online voice related to the topic, not a direct response to the current article.
   https://www.reddit.com/r/developersIndia/comments/1t9v1og/sudden_increase_in_workload_due_to_ai_causing/reddit.com

5. Reddit/r/Futurism "Workers Say AI Is Useless, While Oblivious Bosses Insist It’s a Productivity Miracle"
   Discussion on the usefulness of AI in the workplace. Referencing a comment from a user claiming development experience that productivity increases if AI's limits are understood.
   https://www.reddit.com/r/Futurism/comments/1qni4ph/workers_say_ai_is_useless_while_oblivious_bosses/