AGENTIC AI-BASED AUTONOMOUS IT SUPPORT AND TROUBLE SHOOTING SYSTEM

Abstract

Modern organizations depend heavily on IT infrastructure, applications, networks, cloud services, and employee devices for their daily operations. When technical problems occur, employees generally contact IT support teams through tickets, emails, chats, or phone calls. As the number of users and IT services increases, support teams may receive a large volume of repetitive requests involving password issues, software errors, network connectivity, system configuration, and access problems. The Agentic AI-Based Autonomous IT Support and Troubleshooting System is proposed as an intelligent solution that can understand IT issues, investigate their causes, and perform authorized troubleshooting actions with minimal human intervention. The proposed system uses Agentic AI to go beyond simple question answering. An AI agent can understand a user's problem, collect relevant information, reason about possible causes, select appropriate tools, execute approved troubleshooting actions, and verify whether the issue has been resolved. Natural Language Processing enables users to describe technical problems using ordinary language instead of following complex support procedures. The system can also use organizational knowledge bases, troubleshooting guides, system documentation, and historical support information to improve its responses. The platform can perform different categories of IT support activities, including diagnosing network connectivity problems, identifying application errors, checking system configurations, assisting with account-access issues, monitoring service availability, and recommending appropriate corrective actions. Where permitted, the agent can interact with IT tools and execute predefined remediation workflows. Each action can be governed by authentication, authorization, approval policies, and audit logging to reduce the risk of unauthorized changes. A centralized support dashboard can provide information about active incidents, ticket status, detected problems, troubleshooting actions, system health, and resolution history. The AI agent can automatically create and update support tickets, communicate with users, escalate complex issues to human technicians, and maintain a detailed record of actions performed. This creates a continuous support workflow from issue reporting to diagnosis, remediation, verification, and closure. Overall, the proposed system aims to make IT support faster, more scalable, and more proactive. By combining Agentic AI, knowledge retrieval, tool integration, automated workflows, monitoring, and human oversight, the system can reduce repetitive workload for IT teams while improving user support.