Why do employees feel anxious as AI enters the workplace? Learn the steps employers can take against fear of job loss, inadequacy and being monitored.
A few years ago, artificial intelligence (AI) was on the agenda only of technology companies; today it is entering every corner of the workplace, from the accounting department to the call centre, from the quality control line to the purchasing department. Assistants that summarise reports in seconds, systems that spot a defective product through a camera, software that draws up the shift plan by itself... For management, these tools mean efficiency. For a significant share of employees, the same tools raise the question: "So what will happen to me?" The relationship between AI and the workplace is no longer a technical subject; it has become a psychological one. In this article, for employers, HR managers and factory managers, I look at the anxiety that AI transformation creates in employees, the effect of this anxiety on work, and ways of managing the transformation with people at the centre.
What Do Employees Feel as AI Enters the Workplace?
The arrival of a new technology in the workplace has always required a process of adjustment, but AI feels different from earlier transformations in several ways. A CNC machine or an ERP system took over a specific job. AI, however, also touches work such as writing, analysis and recommending decisions that were long regarded as "uniquely human". For this reason, the feelings that arise in employees are also more complex.
The anxieties most often encountered in the field are as follows:
- Fear of job loss: "If this system can do the job I do, one day they won't need me."
- A feeling of inadequacy and of being left behind: Especially among experienced employees, the thought "I can't learn this at my age" or "The young ones are faster than me".
- Devaluation: The feeling that expertise gained over years will suddenly become unimportant.
- Fear of being monitored and controlled: The worry that performance will be constantly measured by algorithms and that every mistake will be recorded.
- Uncertainty and loss of meaning: Not knowing which work will stay with whom, or how roles will change.
All of these feelings are natural reactions to change. For management to read them as "opposition to technology" or "laziness" is both wrong and a stance that slows the transformation down. Anxiety is often the result of a lack of information and a feeling of losing control.
On the other hand, the picture is not made up of anxiety alone. Many employees also see handing repetitive and tiring tasks over to systems as a relief; less time spent preparing reports, entering data or doing the same check hundreds of times can make room for more meaningful work. Curiosity and worry can exist side by side in the same person. These mixed feelings tip one way or the other depending on how the transformation is communicated. If employees feel that change is something being "done" to them, worry outweighs everything else; if they see that they are part of the change and can acquire new skills, curiosity comes to the fore. For this reason, managers' first task is not to sort employees into "supporters" and "opponents", but to recognise both feelings that everyone carries.
The Effect of AI Anxiety on the Business
In Turkey, employees already enter the transformation process under a high stress load. According to Gallup's 2026 report, 66% of employees in Turkey say they experienced stress during a large part of the previous day, against a global average of 40%. The proportion of employees who are truly engaged with their work is only 8% (Gallup, 2026; 2025 data). When a poorly managed technology transformation is added to this foundation, the following results can follow:
- New tools going unused: The system that was invested in is ignored by employees or run in parallel with the old methods.
- Withholding knowledge: An employee asked to "train" the system that will replace their job may be reluctant to share their work knowledge.
- Presenteeism and burnout: Employees who have to keep up the old work and learn the new at the same time fall into long-term exhaustion.
- Loss of skilled staff: Employees who cannot bear the uncertainty, especially those who could easily find work elsewhere, may leave.
- Safety risks: An operator who does not trust a new automation system, or does not fully understand it, may be inclined to bypass it or to take shortcuts.
In a large survey carried out in Europe, 18% of employees report a lack of autonomy and 26% report poor communication or cooperation within the organisation (EU-OSHA, 2022). When AI projects are badly managed, they magnify exactly these two risk factors: employees feel they have no say in how their work will change and learn what is going on from indirect sources. I discuss separately the relationship between this anxiety and the general feeling of insecurity in the article on job insecurity anxiety.
Organisational Mistakes That Increase Anxiety
Of two companies using the same technology, employees in one may embrace the transformation while strong resistance appears in the other. The difference is usually not in the technology but in how the process is managed. The most common mistakes are as follows:
- Announcing it in the language of "efficiency" and "cost savings": Employees usually hear these words as "headcount reduction".
- Leaving employees out of the design process: Systems built without consulting the people who know the work best both make more mistakes and meet more resistance.
- Limiting training to a one-off presentation: Expecting everyone to use the system after a one-hour introductory meeting.
- Not saying whose role will change and how: Uncertainty leads people to imagine the worst-case scenario.
- Introducing algorithmic monitoring without explaining it: An employee who does not know what data is being collected or for what purpose feels constantly under surveillance.
- Not allowing room to make mistakes: In an environment where mistakes during the learning process are punished, nobody wants to try the new tool.
In an AI transformation, the real question is not how intelligent the system is, but whether people can see a place for themselves within this change.
The Legal and Standards Framework: New Technology Is a Matter for Risk Assessment
The arrival of AI in the workplace is not merely an information technology project but also a change from the point of view of occupational health and safety. Subparagraph (f) of Article 5 of Turkey's Occupational Health and Safety Law No. 6331 requires the employer to develop "a coherent and comprehensive prevention policy covering the effects of factors relating to technology, work organisation, working conditions, social relationships and the working environment". Article 17 of the law provides that occupational health and safety training be given before starting work, when the job or equipment changes and when new technology is introduced, and that it be renewed in line with changing risks.
Article 8 of the Occupational Health and Safety Risk Assessment Regulation also requires psychosocial sources of hazard to be identified and recorded. At the international level, ISO 45003:2021 lists how work is organised as the first category of psychosocial hazards. An AI project in which job descriptions, work pace, decision-making authority and performance monitoring methods change falls squarely within this category. ISO 45003 is not a certification standard but a guideline; however, for organisations with an ISO 45001 system, it offers a framework for including this change in the risk assessment.
The processing of data collected from employees should also be assessed in light of personal data protection legislation. It is advisable to seek the opinion of your legal department or a lawyer on this.
What Can Employers Do to Make AI Fit the Workplace?
To reduce the psychological burden of the transformation, you do not need to slow the technology down; you need to design the process together with people. The steps you can take are as follows:
1. Explain the purpose honestly and concretely. Explain which process is changing and why, which tasks will be automated, and how employees' roles will be transformed. On matters that are not yet known, saying "we don't know yet, and we will make it clear by this date" is far more reassuring than an uncertain silence. Avoid promises that cannot be guaranteed, such as "nobody's job will be affected".
2. Involve employees in the design. In pilot projects, gather feedback from employees on the ground and assess together where the system works and where it falls short. Giving people a voice both improves the quality of the system and reduces the feeling of losing control.
3. Plan learning as a process. Instead of one-off training, run short, repeated, hands-on sessions. A meta-analysis of resilience programmes showed that the effect of one-off interventions declines markedly over time, and that one-to-one and face-to-face group formats are more effective (Vanhove et al., 2016). The same principle applies to learning technology: without reinforcement, learning does not last.
4. Support experienced employees separately. Do not give senior employees the feeling that they are being tested against "innovative" younger colleagues. Including their process knowledge in the set-up of the system shows that their expertise is valued. Offer peer mentoring and the chance to learn at their own pace.
5. Create a safe space for making mistakes. State clearly that mistakes made during the learning period will not be reflected in performance reviews. Team psychological safety, that is, the shared belief among team members that it is safe to take interpersonal risks, was found to be associated with learning behaviour in a foundational study in a manufacturing company (Edmondson, 1999). Learning a new tool requires exactly this kind of risk-taking. You can find more on this in the article on psychological safety.
6. Make monitoring and data use transparent. Share in writing, and in plain language, which data are collected, who can access them and how they will be used in performance reviews. A feeling of surveillance rapidly increases anxiety and mistrust.
7. Prepare managers as carriers of the change. In the World Health Organization's guidelines on mental health at work, the recommendation with the strongest evidence is mental health training for managers (WHO, 2022). Team leaders should be able to notice employees' anxiety, answer their questions and manage their own anxiety too. Remember that managers are also inside the transformation, and their jobs are changing as well.
8. Keep the workload realistic. If employees are working with both the old and new systems during the transition, the length of this period and the extra load should be planned openly, and targets should be adjusted temporarily.
Imagine that an image-processing system is being installed for quality control in a packaging factory. The team that has checked products by eye for years thinks the system will take over their jobs. Management positions this team as the system's "teacher": they decide which defects really matter and where the system goes wrong. The role of the quality control staff changes from examining products one by one to supervising the system's decisions and assessing borderline cases. When this change is explained clearly from the start, the anxiety does not disappear altogether, but employees feel that they are inside the process, not outside it.
How to Get Started in Your Organisation
Organisations that want to manage an AI transformation in a psychologically healthy way can follow a three-stage path:
Needs analysis: The departments and roles that will be affected by the transformation are identified. Through confidential surveys and focus group discussions, employees' level of knowledge, anxieties, learning needs and trust in management are measured. In a study covering workplaces in Europe, the biggest difficulty in managing psychosocial risks was reported, at 59%, to be reluctance to talk about these issues openly (EU-OSHA, 2025). The analysis is the first step towards making the unspoken speakable.
Programme: A communication plan, change and mental health training for managers, hands-on and repeated technology training for employees, cognitive-behavioural stress management workshops and, where needed, confidential individual support are planned together. A meta-analysis examining workplace stress management programmes found that cognitive-behavioural programmes showed a consistently larger effect than other types (Richardson and Rothstein, 2008). You can look at a programme structure suited to your organisation on the corporate services page.
Measurement: The usage rate of new systems, error and near-miss reports, absence, resignations and employee pulse surveys are monitored at regular intervals. Measuring psychological adjustment alongside technological success makes it possible to spot problems before they grow. You can find the wider framework of resistance to change in the article on resistance to digital transformation.
Frequently Asked Questions
Is it normal for employees to be afraid of AI?
Yes. Feeling anxious during a period in which the job, role or expertise will change is a natural reaction. Giving information, giving people a voice and supporting learning, rather than dismissing this anxiety, prevents fear from turning into resistance.
Should an AI project be included in the psychosocial risk assessment?
Every project that changes work organisation, work pace, performance monitoring or roles should be assessed from a psychosocial perspective. Law No. 6331 provides for training when new technology is introduced, and the Risk Assessment Regulation provides for psychosocial hazards to be recorded. Major transformations are therefore a suitable moment to review the risk assessment.
How can we involve senior employees in the transformation?
Use their process knowledge in setting up the system, and offer hands-on training and peer support in which they can learn at their own pace. Seeing that experience has not been devalued, and on the contrary is needed for the system to work properly, makes it easier for senior employees to adjust.
How should I approach an employee who is experiencing intense anxiety during the transformation?
Starting from the changes you have observed, speak calmly and without judgement, share the accurate information you have and offer additional support for learning. If you notice marked disruption in sleep, concentration or daily functioning, or feelings of hopelessness or thoughts of self-harm, refer the employee to a mental health professional; in an emergency, 112 (emergency services in Turkey) should be called. It is also helpful to remind them that seeking professional support is an option for both employees and managers.
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Eda Erkan Alapala
Klinik Psikolog. İstanbul Kent Üniversitesi Klinik Psikoloji Tezli Yüksek Lisans mezunu; bilişsel davranışçı terapi, çocuk merkezli oyun terapisi ve çocuk-ergen psikoterapisi alanlarında eğitimlerini tamamlamıştır.
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