Design and Implementation of an AI-Based Business Intelligence Platform for Human Resource Decision Support

Khaydarova, Malika; Shukurov, Shakhnoza

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Proceedings of International Conference on Applied Innovation in IT · 2026/07/22 · Vol. 14 · Issue 4 · pp. 1103–1110

Design and Implementation of an AI-Based Business Intelligence Platform for Human Resource Decision Support

Malika Khaydarova, Shakhnoza Khaydarova and Akmal Shukurov

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Abstract

The explosion of the digital economy has radically altered human resource management, creating a need for data analysis and analytically supported decision-making. Traditional HR systems relying heavily upon administrative reporting and fragmented data sources are ill-equipped to deal with the complexity and uncertainty involved in workforce management today. This results in the pressing requirement of applied information technology services that incorporate analytics, automation, and intelligent decision-support systems. This paper presents the design and analysis of an AI-based Business Intelligence software platform that supports human resource decision-making in the digital economy. This new platform provides centralized HR data, predictive analytics, and decision-support dashboards from a comprehensive AI-embedded CRM environment to analyze workforce dynamics and managerial outcomes. The research methodology integrates descriptive and predictive analytics in addition to analytical modeling for assessing employee turnover risks, workforce efficiency, and linkages of HR decision-making and organizational goals. The findings indicate that AI-powered Business Intelligence tools can improve analytical transparency, support more consistent workforce planning, and provide quantitative signals for HR decision-making. Predictive indicators support early identification of turnover risk, while interactive dashboards improve the visibility and interpretability of workforce indicators. Consequently, human resource managers can adopt more proactive and evidence-based decision-making practices. The practical importance of the research is in the use case of the proposed BI framework for firms which do business in labour-intensive, flexible contexts. The research theoretical contribution of the study is to facilitate the growth of the role of Business Intelligence and artificial intelligence technologies in human resource management research so that HR analytics will become a strategic contribution in the digital economy for decision-making process.

Keywords

Artificial Intelligence Business Intelligence Human Resource Analytics Predictive Modeling Decision Support Systems Digital Economy

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