The Role of LLM Agent Apps in Conversational AI

Srikanth Vadlamani¹ & Dr. Daksha Borada²

¹Duke University

NC USA

²IILM University

Greater Noida, Uttar Pradesh 201306, India

Abstract

The rapid growth of Large Language Models (LLMs) has tremendously boosted the strength of conversational artificial intelligence applications. In this regard, LLM agent applications have become strong tools for automating and individualizing conversations across industries such as customer service, healthcare, education, and entertainment. LLM agent applications use LLMs to have sophisticated, contextually aware conversations, thereby providing users with a natural conversational experience. Though they have great capabilities, there is a massive research gap regarding the distinctive roles and potential of LLM agent applications in improving conversational AI systems. The goal of this study is to examine the functional roles played by LLM agent applications in conversational AI development and deployment. In a technical specification and user experience feature comparison, this study outlines the unique characteristics that distinguish LLM agent applications from traditional chatbots and other conversational AI designs. The question also highlights the challenges of integrating them, such as the handling of complex user intentions, the guarantee of system scalability, and the resolution of ethical concerns on data privacy and bias. In addition to this, the study aims to improve the process of designing best practices in the deployment and design of LLM-driven agent applications that are able to adapt to evolving user requirements without diminishing ethical and trustworthy interactions. Identifying gaps in research within this context, the manuscript aims to guide the future direction of LLM-based conversational AI technology and applications within different industries for the purpose of improved user satisfaction and interaction quality.

Keywords

LLM agent applications, conversational AI, natural language processing, user experience, chatbot technology, AI integration, ethical concerns, scalable systems, intent detection, conversational automation.

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