How to Cite:
Parimala PR, "Agentic AI Frameworks for End-to-End HR Process Automation" International Journal of Emerging Technologies, Computing and Intelligent Systems, Vol. 1, No. 1, pp. 17-21, 2026.

Abstract:
The rapid advancement of Artificial Intelligence (AI) has transformed Human Resource Management (HRM) from a traditionally administrative function into a strategic business enabler. Recent developments in Agentic AI, characterized by autonomous decision-making, reasoning, planning, memory, and multi-agent collaboration, have introduced a new paradigm for enterprise HR automation. Unlike conventional AI systems that perform isolated predictive or classification tasks, Agentic AI frameworks execute end-to-end workflows with minimal human intervention while continuously adapting to organizational objectives and policy constraints. This research investigates the role of Agentic AI frameworks in automating the complete HR lifecycle, including talent acquisition, employee onboarding, workforce planning, performance management, learning and development, payroll support, employee engagement, compliance monitoring, and offboarding. The study proposes a conceptual Agentic AI architecture integrating Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), workflow orchestration, enterprise knowledge graphs, Human-in-the-Loop (HITL) validation, and secure enterprise databases. A qualitative research methodology based on literature synthesis, comparative framework analysis, and architectural modeling is adopted to evaluate the effectiveness of the proposed approach. The findings indicate that Agentic AI significantly improves recruitment efficiency, decision intelligence, operational scalability, compliance management, and employee experience while reducing repetitive administrative workloads. Nevertheless, challenges related to ethical AI governance, explainability, privacy, algorithmic bias, and regulatory compliance remain critical for successful enterprise adoption. The research contributes a comprehensive framework for intelligent HR automation and provides future directions toward trustworthy, adaptive, and explainable autonomous HR ecosystems suitable for modern digital enterprises.

Keywords: Agentic AI, Human Resource Management, HR Automation, Large Language Models, Autonomous Agents, Workforce Intelligence, Enterprise AI, Digital HR Transformation.

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