Don't Call Me! Why Gen Z and Algorithmic Management Could Be a Perfect Match?
What if young people’s phone phobia isn’t a problem at all, but rather a sign that the workplace is changing? When a third of Gen Z avoid phone calls and half trust AI more than their own manager, perhaps algorithmic management isn’t a threat anymore — but a solution to workplace transformation.
Text Martti Asikainen, 12.12.2025 | Photo by Adobe Stock Photos
According to a recent survey by Trinity College London, approximately 30% of British Gen Z workers, or ‘zoomers’, suffer from a fear of making phone calls, known as ‘telephobia’ (Trinity College 2025). The study interviewed over 1,500 people aged 16–29. It also revealed that 38% of respondents found workplace small talk distressing, and as many as 60% consciously avoid working with older colleagues.
This is far from an isolated observation. According to a survey published earlier this year by Zero Bounce (2025), email is Gen Z’s absolute favourite way to communicate, whilst only 2% preferred video calls and 7% phone calls. Perhaps even more revealing is that as many as 60% admit to using email specifically to avoid conversations and confrontations.
These figures don’t indicate laziness. They tell us about a generation that has grown up communicating asynchronously, in writing, and thoughtfully. And it is precisely these characteristics that make them perhaps the first generation truly compatible with algorithmic management. It’s therefore no surprise that nearly half of Gen Z professionals prefer to rely on AI guidance rather than their manager at work (TalentLMS 2024).
Why Text Beats Talking for Gen Z
Imagine a scenario, where a 24-year-old marketing assistant sits at their desk, focused on analytics, when suddenly the phone rings. Their manager wants to discuss last week’s project. The conversation requires immediate response, quick thinking, and the ability to handle potential criticism in real time whilst keeping the discussion professional.
For Gen Z, this experience can be more stressful than for older colleagues, as they don’t have time to prepare, check facts, or consider their response. The mere thought of saying something wrong or sounding foolish can trigger anxiety. An algorithmic system could fit this type of work environment like a glove.
An algorithmic manager operates differently. A task appears in the app as clear text, showing the deadline, criteria, and objectives. Feedback comes as data rather than a surprise phone call, allowing the employee to read the message and respond at their own pace. No panic, interruptions, or spontaneous performance pressure (Jarrahi et al. 2023).
Gen Z is the first generation to grow up in a world where most social interaction takes place through text. Digital natives favour short, informal messages such as emojis, abbreviations, and sentence fragments (Corporate English Solutions 2024). For digital natives like them, this behaviour isn’t a sign of unprofessionalism, but of efficiency.
Fairness Without Prejudice
Research by Haaga-Helia University of Applied Sciences shows that employees often perceive algorithm-based management as fairer than human management (Asikainen & Lahtinen, 2025). Younger employees in particular respond positively to systems that treat everyone the same way based on data.
Young people’s attitude may also stem from the zeitgeist. Gen Z, having grown up amidst DEI discussions, has developed a strong sense of fairness. They know that people have favourites, prejudices, and bad days. An algorithm, however, doesn’t care whether you’re an introvert or an extrovert. It won’t give you a lower performance rating because you skipped the Friday pub quiz, or promote someone else because they share the manager’s passion for golf.
The full picture, however, isn’t that simple. If an algorithm is trained on biased data, it systematically reproduces prejudices (Hirsch et al. 2023). Amazon’s recruitment algorithms are perhaps the most well-known example. They discriminated against women because the training data primarily contained successful male applicants (Dastin 2018).
New Control, New Problems
If algorithmic management promises fairness and asynchronous communication, why isn’t it a universal solution? Because flexibility comes with a hidden cost. Research shows that flexibility is more important to Gen Z than any other factor when choosing a workplace (Jabra 2024; Gentile 2025; Deloitte 2025). As many as 68% want to work from home (Trinity College 2025). All of this is easier to implement with an algorithmically managed system, but it can create a new kind of problem.
Algorithmic management may reduce the sense of autonomy, employees’ opportunities to decide how their work is carried out, and increase workload (Zayid et al. 2024; Jensen et al. 2024). At the same time, continuous data collection—login times, response speeds, task volumes — can create an even more oppressive form of control.
Excessive reliance on text-based communication can also be a harmful coping strategy that reinforces social anxiety in the long term (Zero Bounce 2025). Systematically avoiding phone calls and face-to-face conversations can lead to a situation where an employee never learns to handle them. Working life, however, requires the ability to negotiate, influence, and resolve conflicts within a team.
Balance, Not Extremes
When discussing Gen Z and algorithmic management, one inevitably asks whether we are normalising a working life where people no longer need to learn social skills, and what the long-term impact will be on society if multiple generations avoid direct interaction with colleagues and managers.
On the other hand, we must bear in mind that not all zoomers fit the same mould. Some love talking on the phone, others enjoy spontaneous meetings. Some hate making calls, and others hate meetings. If we build working life based on stereotypes, we marginalise everyone who doesn’t fit the mould.
Let’s return for a moment to the 24-year-old marketing assistant whose phone rings during the workday. Perhaps they don’t need fewer phone calls, but better-timed ones. Maybe the algorithm isn’t a threat to their development, but a tool that frees them to focus on what truly requires human expertise. Is Gen Z’s phone phobia a problem that needs fixing, or the first sign that working life is changing?
Rather than trying to force young people into the old world’s moulds, we should ask ourselves what phone calls are really needed for, and whether they’re needed at all. Perhaps the future of work isn’t either-or, but both-and: algorithms manage routines, humans create meaning. The question isn’t whether to embrace algorithmic management, but how to implement it without losing what makes us human — the ability to navigate ambiguity, build trust, and have difficult conversations when they matter most.
References
Asikainen, M., & Lahtinen, A. (2025). Algorithmic management spreads across Finnish workplaces – younger workers show greater acceptance than their older colleagues. Haaga-Helia University of Applied Sciences. Published on 16 June 2025. Retrieved 10 December 2025.
Corporate English Solutions (2024). Navigating Gen Z’s communication style in the workplace. British Council. London. Retrieved 10 December 2025.
Dastin, J. (2018). Amazon scraps secret AI recruiting tool that showed bias against women. Published in Reuters on 11 October 2018. Retrieved 10 December 2025.
Deloitte. (2025). Gen Z and Millennial Survey. Growth and the pursuit of money, meaning, and well-being. Deloitte Touche Tohmatsu Limited. Retrieved 10 December 2025.
Gentile, A. (2025). Generation Z work preferences: The focus of recent student/faculty research. Published on Pace University website 9 April 2025. Retrieved 10 December 2025.
Hirsch, F., Alizadeh, A., Wiener, M., & Benlian, A. (2023). The Uberization of work: Non-platform workers’ perceptions and legitimacy judgments of algorithmic control. In ICIS 2024 Proceedings.
Jabra. (2024). Mind the Gap. How Gen Z is disrupting the workplace in 2024. Retrieved 10 December 2025.
Jarrahi, M. H., Möhlmann, M., & Lee, M. K. (2023). Algorithmic management: The role of AI in managing workforces. MIT Sloan Management Review, 1–5.
Jensen, M. T., Oosterwijk, G. R. & Nørgaard, A. S. (2024). Computer in Command: Consequences of Algorithmic Management for Workers (Policy Study). Foundation for European Progressive Studies (FEPS).
TalentLMS. (2024). How AI impacts Gen Z in the workplace. Retrieved 10 December 2025.
Trinity College London. (2025). Career-Ready: Bridging the employability skills and confidence gap. London. Retrieved 10 December 2025.
Zayid, H., Alzubi, A., Berberoğlu, A., & Khadem, A. (2024). How Do Algorithmic Management Practices Affect Workforce Well-Being? A Parallel Moderated Mediation Model. Behavioral Sciences, 14(12), 1123.
ZeroBounce. (2025). Gen Z at work – The 2025 report. Retrieved 10 December 2025.
Martti Asikainen
Communications Lead
Finnish AI Region
+358 44 920 7374
martti.asikainen@haaga-helia.fi
This article is published as part of Haaga-Helia University of Applied Sciences’ “RoboBoss — AI in Expert and Knowledge Work Management” project, which examines algorithmic management in expert and knowledge work. The areas where AI’s role has thus far been studied and understood only to a limited extent. The project’s main funder is the Finnish Work Environment Fund.
Finnish AI Region
2022-2025.
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