Ai For Customer Support: Scaling Tier 0 Agents With Intelligent Automation

Abstract

The fast pace of integrating artificial intelligence (AI) into enterprise customer care has enabled the introduction of so-called Tier 0 agents, or automation systems that do not interact with a human operator and instead address frontline inquiries. This article scrutinizes the necessary technical and operational frameworks for the successful implementation of high-performance Tier 0 agents. The topic of reinforcement fine-tuning with golden datasets and the usage of Retrieval-Augmented Generation (RAG) to reduce the number of factual errors. The article looks at important measures of success, including confidence scoring and the ability to resolve issues without emotions, along with economic indicators that show productivity can improve by up to 35 percent for certain worker groups. Finally, the article presents a safety-focused architecture that utilizes the NIST AI Risk Management Framework and iterative machine learning best practices. The results indicate that effective Tier 0 implementation will convert the customer support from a reactive cost center to a proactive, scalable strategic asset.