Automating Enterprise IT Support: Design and Evaluation of an Autonomous AI Agent

In the rapidly evolving digital enterprise landscape, maintaining efficient and responsive IT support is critical for business continuity and user satisfaction. However, traditional support models that rely heavily on human agents frequently suffer from high operational costs, limited scalability, and slow resolution times for routine issues. To overcome these challenges, this paper presents the design, implementation, and evaluation of an autonomous, AI-powered IT Support Agent built to automate and enhance technical support services. By leveraging advanced natural language processing (NLP), machine learning, and deep integration with an enterprise knowledge base, the proposed system can intelligently interpret user queries, diagnose common technical problems, and provide real-time solutions without human intervention. The developed agent autonomously handles repetitive Tier-1 tasks such as password resets, software troubleshooting, network diagnostics, and automatic ticket generation. Crucially, the architecture includes an escalation module that seamlessly transfers highly complex issues to human technicians while preserving the complete context of the user's interaction. Implementation results demonstrate that the system continuously learns from user interactions to improve its accuracy over time. By deploying this AI-driven support ecosystem, organizations can significantly reduce response times, lower operational costs, and offer continuous 24/7 support. Ultimately, this solution vastly improves the overall user experience and organizational productivity while allowing human IT staff to dedicate their expertise to more complex, strategic initiatives