Towards Intelligent Human Resource Management: An Agentic AI Approach with Embedded Analytics

This article presents a multi-agent system with AI capabilities as both a modular, multi-agent system and attempts to the end-to-end model of recruitment by automating and simplifying the process. The architecture that is designed is premised on autonomous agents, working together to process documents, draw skills, assess candidates, and offer data-informed decision support. The system is also capable of mapping unstructured job description and resume information to meaningful skills and experience and keywords using Optical Character Recognition (OCR) and Large Language Models (LLMs). Candidate-job similarity scores are computed through a Skill Matching Agent, and adaptive, skill-focused tests are produced by a generative AI-based Test Generation Agent. The answers of the candidates are collected with the help of an interactive interface and analyzed with the help of an integrated analytics module, which displays performance metrics, visual reports, and leaderboards. The technology results in an HR Decision Hub that integrates the insights in clear and effective shortlisting of candidates. It is experimentally established that the model enhances precision of recruitment, reduction of bias, and operational effectiveness in hiring talents.