RAG Agentic AI as Digital Frontline in Service-Based Organizations: A Systematic Literature Review - Najmi Khairunnisa; Riska Dhenabayu; Syahda Hati Dendra (Universitas Negeri Surabaya, 2026)
This study systematically reviews the development of Agentic AI as digital frontline systems within service-based organizations. The increasing adoption of artificial intelligence in organizational environments has accelerated the implementation of conversational systems capable of supporting consultation workflows, operational communication, and information delivery processes. However, conventional chatbot systems still experience limitations related to contextual understanding, reasoning capability, and multi-step task execution. To address these limitations, recent studies increasingly integrate Agentic AI and Retrieval-Augmented Generation (RAG) to support more adaptive and context-aware conversational systems. This study employed a Systematic Literature Review (SLR) approach following the PRISMA guidelines. Literature selection was conducted using several academic databases, including Scopus, IEEE Xplore, ACM Digital Library, ScienceDirect, and Google Scholar. After the screening and eligibility process, 61 articles published between 2020 and 2026 were selected for final review and analyzed using thematic synthesis. The findings identified three dominant research themes consisting of Agentic AI architectures and autonomous systems, Retrieval-Augmented Generation and conversational intelligence, and deployment of Agentic AI in digital frontline systems. The review demonstrates that Agentic AI integrated with retrieval-enhanced conversational mechanisms has strong potential to support contextual interaction, consultation workflows, and organizational communication processes within service-based environments. Nevertheless, several challenges remain related to hallucination, governance, trustworthiness, evaluation reliability, and real-world deployment complexity.