Artificial Intelligence for Employee Engagement and Well-Being: A Review of Digital Tools, Psychometric Measures and Workforce Sentiment Datasets in Modern HR Systems

Artificial intelligence (AI) is rapidly transforming how organizations monitor, predict, and enhance employee engagement and well-being. This paper assesses empirical and conceptual evidence from 2015–2025 across three interconnected domains of modern HR analytics: AI-driven digital engagement and well-being tools, psychometric measures embedded in AI systems, and real-world workforce sentiment datasets used for model development and validation. Following PRISMA guidelines, the paper integrates findings from major scholarly databases and industry sources to examine emerging technologies such as transformer-based NLP models, predictive HR systems, wearable biometric platforms, conversational coaching AI, and digital exhaust analytics. Results show that advanced AI models, particularly RoBERTa, XLM-R, and GPT-based classifiers, achieve high accuracy in sentiment and engagement prediction, while hybrid multimodal models combining text, behavioral metadata, and physiological signals outperform traditional structured-data approaches. Psychometric instruments including the Gallup Q12, UWES, PERMA, PANAS, and CBI remain essential for providing validated constructs and improving the interpretability and scientific rigor of AI-generated insights. The study also highlights the growing importance of large-scale datasets such as Glassdoor reviews, IBM HR Analytics, and enterprise wearable logs in enabling robust benchmarking and model generalizability. Despite rapid technological progress, challenges persist related to algorithmic bias, data governance, cross-cultural variability, and ethical deployment of emotion-aware systems. The paper concludes by emphasizing the need for responsible AI design, multimodal data integration, and stronger psychometric-AI alignment to build trustworthy, employee-centered HR ecosystems capable of supporting well-being, organizational resilience, and strategic workforce decision-making.