Agentic Artificial Intelligence in Enterprise Transformation: Tenets, Architectures, and an HR-Centric Case Study on Profile Augmentation

Abstract

Agentic Artificial Intelligence (AI) is the emerging paradigm in which autonomous software agents coordinate reasoning, tool use, retrieval, and actuation to pursue enterprise goals. We present a research-grounded and practice-ready treatment of agentic AI for the enterprise, with Human Resources (HR) and recruitment as the primary locus of application. The paper synthesizes recent advances in large language models (LLMs), retrieval-augmented generation (RAG), and vector similarity search, and operationalizes them through an agentic architecture deployed for resume parsing, profile augmentation, and candidate–job matching. We report a development roadmap, acceptance criteria, and partner validation plan derived from a production case. We close with governance patterns for bias, privacy, and explainability, and a forward look at multi-agent orchestration across the employee lifecycle.