Employees suffering because their boss abuses AI, have they "asked ChatGPT about everything?"

(Dan Tri) - Many managers put absolute trust in AI, making employees frustrated because they have to both meet the increasing workload and bear the responsibility of fixing errors created by AI.

“Have you asked ChatGPT yet?”

Every time a communication plan is completed, instead of receiving feedback from superiors, Phuong Thao (24 years old, Hanoi), a content marketing employee, receives feedback generated by AI.

According to Thao, her whole team often takes many days to research data, balance budget, personnel, build implementation schedules and calculate options suitable to reality.

Instead of receiving feedback based on the experience of superiors, many elaborate plans and reports from employees only receive feedback generated by AI (Illustration photo: Tuan Anh).

"If you read it, you'll immediately know that the boss hasn't really looked at the plan but just sent AI to comment on it for you. What annoys me the most is the fact that superiors use AI to avoid the responsibility of reading, thinking and criticizing employees' efforts," Thao said.

In particular, after each AI edit, Thao became even more tired when just a few days later, her boss asked her to edit again because "the AI ​​thought of another idea".

"Many times, the boss even says that just add AI for a few minutes and it's done. But they don't consider that AI is not responsible if the project fails," she expressed.

Constantly having to edit results according to suggestions generated by AI makes many employees feel pressured and tired (Illustration: Tuan Anh).

Thao said that managers not only use AI to respond to reports, but almost all content before being sent is required by superiors to be put through chatbots for checking.

Even when AI suggests options that are not consistent with the platform's policies or the company's situation, superiors still prioritize trusting chatbots over employees.

A similar situation also occurs at the company where Thanh Huyen (22 years old, Hanoi), a content marketing employee, is working.

According to Huyen, after each media campaign on Facebook or TikTok, the platforms automatically provide a fairly detailed reporting and analysis system on content effectiveness, viewership or advertising costs.

However, the superiors did not rely on this data and the experience of the marketing team but entered all the data into ChatGPT to draw conclusions and decide on the next strategy.

Not relying on their own experience and employees' professional opinions, some managers choose to prioritize AI recommendations when making decisions (Illustration: Tuan Anh).

"If the AI ​​says to stop advertising, the boss also asks to stop. If the AI ​​says to change direction, the whole group has to follow, with almost no objections," Huyen recounted.

For Huyen, the thing that makes her feel most pressured is that all her professional opinions can be easily rejected if they differ from the results given by the AI.

"Many times my boss criticized me and my colleagues for writing content that was not as deep or good as ChatGPT, so they decided to choose articles created by AI," Huyen confided.

Not only that, the female employee also encountered some frustrating situations when she asked her superiors about the problem, the answer she received was only: "Have you asked ChatGPT?".

The employee has to fix the error caused by the boss's AI

Besides relying on AI to make decisions, some managers also delegate complex data processing processes with the expectation of saving more time.

My Duyen (22 years old, Quang Ninh), an employee at an English center, said that in the past, she had meticulously compiled and processed transcripts on Google Sheets so errors rarely occurred.

However, since her boss started looking to buy the ChatGPT Plus package, the process changed completely.

After the employee enters the original scorecard, all data will be uploaded to AI by superiors to automatically process, analyze, and create rankings with beautiful colors and layouts.

Since her superiors placed too much trust in AI, My Duyen has repeatedly been helpless when she had to constantly help her boss correct errors created by this tool (Illustration: Tuan Anh).

"It looks more professional and lively, but many times the AI ​​places the wrong class, is missing student names, or displays incorrect information, and as a result, the center receives a series of bad feedback," Duyen said.

Notably, after making mistakes, her superiors continued to use AI in this job and required employees to open each board for review before sending it to learners.

My Duyen shared: "There are days when having to review and update each case takes a lot of time. In the past, I even did it manually myself, sometimes faster than AI."

According to her, bosses using AI in everything happens more and more often, but in the end the person who has to check and be responsible for correcting if there are errors is always the employee.

"Once my boss sent me a data synthesis form created by ChatGPT with eye-catching images and the saying: "You're about to be unemployed, Duyen, AI will do it in a bit." It sounds like a joke, but it really makes me very upset," Duyen said.

The case of Huyen Mai (22 years old), a new marketing graduate, is even more special.

She said that in the first month of working, she was surprised to constantly hear questions like: "Learn AI, now AI can control the entire marketing department", "If you haven't asked AI yet, why not ask me?" or "I manage all social networks and communities. I already have AI so it's light."

Many managers assume that AI can replace employee labor, thereby increasing workload, requiring employees to take on more tasks with the excuse that "AI has done it all" (Illustration: Tuan Anh).

While the workload is increasing, every time she reflects on the overload, she receives the answer: "AI has done it all".

The fact that managers assume AI can completely replace employees' labor and thinking makes Mai increasingly exhausted as she has to constantly prove her productivity.

The more CEOs trust AI, the more exhausted their employees are

The above stories reflect the growing gap between leaders' expectations and workers' actual experiences.

This is evidenced by research conducted by Stanford University and BetterUp Labs on 1,150 full-time employees in the US, showing that AI does not bring the expected efficiency but also creates the "workslop" phenomenon.

That is the situation where AI-generated content seems neat on the outside but lacks depth, lacks context, and is not of good enough quality to get the job done.

Instead of saving time, the fact that content creators only need to enter commands and transfer the results from AI to colleagues causes the recipient to have to re-read, verify, correct errors or start over.

According to the survey, nearly 20% of this phenomenon originates from superiors, resulting in many employees being tired of spending extra hours handling these errors.

Another study by ActivTrak on more than 10,500 users within 180 days before and after AI application also showed results contrary to expectations.

Research shows that using AI not only does not help reduce but also causes time spent on work tasks to increase sharply from 27% to 346%.

Specifically, time spent processing repetitive tasks such as email increased by 104%, chat and texting activities increased by 145%, and time spent using task management tools increased by 94%.

What's more, this report also doesn't note any groups of activities where AI actually helps users save time.

Contrary to expectations of making work easier, AI causes employees to multitask more and spend less time on complex tasks that require deep concentration.

Even due to pressure from superiors to use AI to create high productivity, many people experience "brain burn", which means mental fatigue due to using or monitoring AI beyond cognitive ability.

Steve McGarvey, a user experience designer in North Carolina (USA), believes that many leaders today are assuming AI is the "savior".

However, if you do not have the ability to judge or have expertise in your field, trusting AI completely can harm the user or negatively affect the entire work group.