The integration of Artificial Intelligence (AI) analytics in Human Resource (HR) hiring is transforming recruitment from a conventional, time-consuming process into a data-driven and strategically efficient function. This study explores how AI analytics revolutionizes talent acquisition by automating candidate screening, predicting cultural fit, and enhancing decision-making accuracy. Beyond immediate efficiency gains, AI-driven hiring systems offer long-term economic value by reducing turnover costs, minimizing recruitment errors, and ensuring the timely acquisition of top talent critical for organizational competitiveness. The future of HR hiring will increasingly rely on predictive analytics, natural language processing, and machine learning algorithms to not only assess technical skills but also anticipate employee performance, adaptability, and retention potential. By examining current practices and future advancements, this research seeks to provide actionable insights for organizations striving to leverage AI as a strategic tool to attract, select, and retain the best talent in an evolving global workforce. This study emphasizes the economic implications of adopting AI in HR—highlighting cost savings, improved productivity, and enhanced employer branding The researchers in their research aims to identify how AI analytics can balance efficiency with fairness, ensuring unbiased hiring practices while supporting organizational growth in a knowledge-driven economy