Artificial intelligence (AI) is a field of computer science focused on developing systems that can perform tasks typically associated with human intelligence, such as learning, reasoning, decision-making, pattern recognition, and language processing (García-Madurga et al., 2024). By analyzing large datasets and identifying meaningful patterns, AI systems are increasingly applied to complex organizational challenges, including workplace well-being. The relevance of such applications is underscored by the growing prevalence of mental health conditions among employees, with more than 40% of sickness benefit claims attributed to mental or behavioral disorders (Cahill et al., 2021).
One central contribution of AI lies in its capacity for continuous monitoring and early detection of psychological strain. AI systems can analyze real-time indicators such as mood, stress, and fatigue to generate personalized feedback and self-care recommendations (Chang, 2020). At the same time, aggregated insights can support line managers in identifying emerging patterns of strain within teams and responding proactively.
In addition to sensor-based monitoring, AI can also interpret communicative and behavioral data to assess mental health trends. Hoque Tania et al. (2022) explore the application of sentiment analysis to understand how individuals express emotions related to work and health in real time. These approaches collectively position AI as a predictive tool capable of identifying psychosocial risks before they escalate.
However, detection alone is insufficient without supportive intervention. AI technologies can also provide direct emotional assistance through chatbots and intelligent messaging platforms that offer conversational guidance and basic counseling (García-Madurga et al., 2024). Such tools increase accessibility to support services and may reduce barriers associated with stigma or limited resources.
Building upon monitoring and emotional support, AI also enables the development of personalized wellness initiatives. Through mobile applications and wearable technologies, continuous health data can inform targeted interventions such as ergonomic adjustments and injury prevention strategies (Cahill et al., 2021).
Finally, AI contributes to workplace well-being through education and skill development. AI-driven training systems can deliver personalized learning experiences that strengthen coping strategies and resilience. Howard (2019) examines the use of AI-supported virtual reality simulations that recreate hazardous work scenarios in immersive environments.
Overall, the literature suggests a progressive integration of AI in workplace well-being strategies. When implemented responsibly and combined with human oversight, AI has the potential to contribute to more proactive, comprehensive, and sustainable approaches to employee mental health and organizational well-being.