AI at Work: Effects on Employee, Well-Being, Learning, And (Un)Ethical

Artificial intelligence (AI) is increasingly seen in the form of digital assistants, generative systems, decision-support tools, and workflow automation in the modern workplace. Although AI is recognized for its impact on productivity and efficiency, its implications for employees’ well-being, learning in the workplace and ethical behaviour, offer complexities and depend on the context. This study examines how AI usage at work affects these three critical employee outcomes. In particular, we are interested in whether more AI adoption simply results in better experiences for employees or introduces new challenges for organisations. The study utilizes a quantitative, cross-sectional design using primary data acquired from 188 respondents by means of a structured questionnaire. The independent variable is the use of AI, while employee well-being, workplace learning, and (un)ethical behaviour form the dependent variables. The results of the data processing performed on SPSS for this study involved the application of descriptive statistics, reliability analysis, correlation, and regression to examine the relationship between the variables that have been used in the study. The results show that AI usage, employee well‑being, workplace learning and ethical issues are perceived at the moderate level. Nonetheless, the findings reveal no correlation between the usage of AI and the three outcome variables. The regression results show that AI use explains very little variance in employee results meaning that simply using AI either occasionally or often does not bring about any significant change. The findings emphasize the significance of mediating factors such as organizational support, leadership involvement, training, task-technology fit, and governance mechanisms. Furthermore, the study reveals moderate ethical risks pertaining to verification, responsibility, and accountable and responsible usage of AI. The measurement scales’ low reliability scores suggest that the results should be interpreted in an exploratory manner, contributing to a call for better instruments in future research. Thus, one conclusion to be drawn from the study is that AI should not be reduced solely to a technology that increases productivity. Instead, it should be treated as a socio-technical construct, requiring a proper organisation of implementation, ethical oversight and continuous development of employees. To ensure that AI can enhance employee well-being and learning, organizations should focus on creating a supportive environment, strengthening AI literacy and establishing ethical guardrails, among other priorities.