Vol. 7, Issue 2, Part G (2025)

Employee wellness has become front and center in recent years as a key driver in organizational success, affecting things like productivity, retention and overall happiness in the workplace. Conventional means of measuring employee morale and engagement think surveys and feedback forms can offer a narrow and time-delayed perspective. Welcome to the age of AI and NLP where businesses now have the opportunity to start receiving real-time actionable information about the way their employees are feeling, finally able to close the gap of how far behind they have been when it comes to accurately managing the health and safety of the workforce. We're looking into combining AI-based sentiment analysis techniques to monitor and evaluate employee well-being and happiness. The study utilises sentiment analysis, powered by artificial intelligence, to analyse extensive amounts of employees’ texts: emails, chat, feedback forms and social media. This unstructured data can be processed by AI algorithms to determine trends in sentiment, and infer what problems, if any, are preoccupying or demotivating employees. Results of the sentiment analysis are then analyzed, providing users with the entire picture of the emotional climate in the workplace, so they can act before problems such as stress, burnout, dissatisfaction and disengagement emerge. Apart from identify emotions, the AI based system is also designed to propose actions to improve employee well-being based on the trends detected. It can, for example, suggest certain interventions, whether in the form of wellness programs, leadership development or even organization policy changes. Constantly assessing and addressing the way workers feel then lets companies tweak and fine tune their systems more to their liking over time, ultimately leading to higher worker satisfaction rates, decreased turnover rates, and generally a happier place of employment. This paper further discusses out ethical considerations and problems arising from AI-facilitated sentiment analysis, including data privacy, the consent and potential biases of AI systems. Finally, the study underscores also the importance of employing AI tech in combination with human context to ensure that the insights gained from the analyses conducted on the data facilitate an inclusive and harmonious workplace.