Smarter HR Decisions with AI: A Predictive–Adaptive Cloud HCM Framework for Workforce Transformation

The incorporation of Artificial Intelligence (AI) technology into Human Capital Management (HCM) solutions has the potential to revolutionize the way organizations manage their workforce. HCM solutions enabled with Artificial Intelligence technology can effectively process workforce data in real-time through complex machine learning techniques. This will provide a predictive model to resolve issues such as employee retention, workforce management, and employee engagement. In this study, a predictive and adaptive human capital management framework has been proposed. This framework will include continuous learning, fairness, and decision support. Experiments were conducted on the proposed model using real-life human resource data. The results showed that the model can predict with a high accuracy of up to 94%, improve employee retention up to 15%, and reduce the hiring time by up to 20%. Moreover, the results of fairness assessment demonstrate that the level of bias among different demographic groups is reduced by more than 50%, and the level of system latency remains less than 400 milliseconds, even with the processing of workloads involving up to 100,000 employees. Furthermore, the results of the ablation study underscore the importance of the aspect of governance, along with feedback loops, for the sustainability of the effectiveness of the models. Thus, the results of the present study demonstrate that the proposed approach has the potential to offer better technical as well as ethical alignment, thereby providing a promising way forward for more intelligent, transparent, and outcome-oriented HR management.