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Artificial Intelligence (AI) is at the center of many debates today, including its use in professional contexts. Is it an effective way to boost productivity? Does it risk replacing human relationships and undermining social bonds? Can it relieve employees of repetitive tasks, or does it instead create cognitive overload, stress, and insecurity?
These are important questions that deserve a closer look—particularly when it comes to the opportunities AI offers and the challenges to overcome in relation to mental health at work.
Have you ever imagined that AI could be a tool to improve employee well-being? In fact, it offers valuable opportunities to reduce mental load and detect at-risk situations. Let’s look at how AI can help prevent and manage psychosocial risks in the workplace.
Some researchers suggest it is possible to detect early signs of burnout or declining mental health using AI. By analyzing digital behavior data, machine learning algorithms can spot unusual patterns in the use of workplace tools: longer connection times, late-night emails, or sudden drops in productivity.
This rapid, large-scale data collection can be a powerful support for managers and HR teams, providing objective indicators of employee fatigue or overload. These signals allow for early dialogue, before the situation escalates into full burnout.
AI can also analyze employee survey responses and interactions on collaboration platforms, highlighting weak signals such as declining engagement, loss of motivation, or rising stress.
In 2022, a study led by Professor Mascha Kurpicz-Briki demonstrated an effective AI-based method to detect burnout. By combining relevant data and training AI models, the approach correctly identified 93% of burnout cases based on open-text responses.
AI remains a tool, not a replacement for human intervention. It can spot trends and raise alerts that support preventive actions: adjusting workloads, HR interventions, or offering psychological support.
But AI cannot fully interpret emotions, personal contexts, or team dynamics, which are often underlying causes of burnout. Declining mental health cannot be reduced to a drop in productivity or shifts in digital habits—it requires a more nuanced analysis, involving HR, managers, and potentially occupational psychologists.
Addressing mental health at work often faces obstacles: lack of time, generic support content, and persistent stigma that prevents open dialogue.
Here, AI can help provide highly personalized support. By analyzing patterns of stress or fatigue unique to each employee, AI can suggest tailored recommendations: workload alerts, timely break reminders, or easier access to specific resources.
Chatbots and virtual assistants can also guide employees toward resources relevant to their situation.
Recent studies even suggest chatbots could serve as therapeutic tools. For example, researchers Michael Heinz and Nicholas Jacobson conducted the first clinical trial of a generative AI-based therapeutic chatbot. Among 106 participants experiencing depression, anxiety, or eating disorders, results showed:
Participants also reported having as much trust in the chatbot as in a human therapist.
According to a 2025 study published by Harvard Business Review (How People Are Really Using Gen AI in 2025), the most common use case of ChatGPT today is mental health support (therapy and companionship). This reflects the immense need for safe, stigma-free spaces to talk.
Still, clinical and human supervision remains indispensable. AI should not replace therapists or managers, but serve as a complementary tool in workplace mental health support.
AI may prove valuable for workplace mental health—when used in a secure framework that protects employee data. But we must also ask: is it truly risk-free? Let’s look at the main risks and challenges for healthy, effective adoption of AI in the workplace.
AI relies on analyzing large volumes of sometimes sensitive data, raising legitimate concerns about confidentiality. Employees may wonder: who has access to their data, for what purpose, and how is it used?
Beyond individuals, companies themselves are at risk: without a clear framework, internal data (strategic, HR, or operational) could be exposed.
This makes it essential for organizations to:
AI’s growing role in the workplace can create anxiety about job security. The fear of being replaced by technology can lead to chronic stress and decreased motivation.
As automation extends from repetitive tasks to some cognitive functions, employees may worry their roles will become obsolete. This can push some to adopt unsustainable work paces to prove their value, increasing risks of overwork, stress, and fatigue. Others may resign themselves, believing their efforts are futile against inevitable technological change.
The pressure of productivity is not new—but AI intensifies it. Algorithms can now analyze performance in real time, tracking metrics like production rates, deadlines met, or time spent on micro-tasks.
For employees, this can feel like being under continuous monitoring, compared to dehumanized algorithmic standards. Such perceived surveillance heightens stress and undermines trust, especially when it concerns sensitive topics like mental health.
While AI can relieve employees of repetitive tasks, it can also increase cognitive load. Why? Because using AI effectively requires training: learning how to use it, adapting to rapidly evolving tools, and navigating ethical and performance-related expectations.
Instead of reducing stress, AI adoption can risk adding to existing workloads, unless carefully managed.
As AI becomes essential in many sectors, workplace mental health specialists must ask: how can it be integrated in ways that enhance well-being and performance, while managing the stress and risks it creates?
Lack of knowledge and misconceptions about AI fuel fear and anxiety among employees. Clear and transparent communication is key. Organizations should:
This transparency reduces speculation and fosters trust.
It is also valuable to create spaces for dialogue where employees can ask questions, voice concerns, and share experiences. Such discussions strengthen acceptance and confidence.
Finally, training is crucial—not only in using AI tools but also in change management. Providing opportunities to upskill or reskill helps employees view AI as a chance for growth, rather than a threat.
A successful integration of AI also requires a workplace culture centered on well-being. Employees need to feel they can rely on managers and leadership for support and empathy.
This includes:
Here again, teale’s workplace well-being solution is a valuable ally. Through its application, expert-led programs, and Joy, its specialized and secure AI assistant, teale helps employees:
