The rapid integration of Artificial Intelligence (AI) into organizational systems has significantly transformed the way human resources are managed, particularly in the dynamic retail sector. This study explores how robo-advisory technologies—AI-driven decision-support systems—can bridge the gap between human capital and economic efficiency in Human Resource Management (HRM). In an industry characterized by high employee turnover, fluctuating consumer demand, and the growing prevalence of gig and part-time workforces, there is an increasing need for intelligent and sustainable workforce strategies. The primary aim of the researcher is to examine the economic implications of adopting robo-advisory tools in HR functions such as recruitment, workforce scheduling, performance evaluation, and employee retention within retail organizations. The study adopts a conceptual and analytical approach, integrating insights from HR analytics, labour economics, and digital transformation frameworks. It highlights how AI-enabled systems can support data-driven decision-making, optimize labour costs, enhance productivity, and ensure better alignment between employee capabilities and organizational goals. The findings suggest that robo-advisory driven HRM can contribute to sustainable workforce management by reducing operational inefficiencies, minimizing human bias in decision-making, and promoting fair and transparent HR practices. At the same time, the study acknowledges potential challenges, including technological dependency, ethical concerns, and the need for continuous upskilling of employees to adapt to AI-driven environments. The researchers in their research emphasizes that the successful implementation of intelligent HR systems in retail depends on a balanced integration of technology with human intelligence.