Bank of America's AI strategy exemplifies the benefits of using small, task-specific language models (SLMs) over large language models (LLMs) in enterprise environments, highlighting the success of Erica, a lightweight AI agent designed for precise, efficient customer interactions. Erica's implementation leverages Graph Retrieval-Augmented Generation (GraphRAG), which enhances performance by providing structured, transparent, and rapid context retrieval, significantly reducing latency compared to traditional methods. Despite the challenges of scaling AI agents, such as domain overfitting and maintaining compliance, GraphRAG offers solutions like stateful context storage and transparent data lineage, essential for audits and regulatory adherence. Bank of America's significant AI investment underlines the importance of smart architecture over sheer model size, combining in-house expertise with advanced retrieval systems for tailored, compliant, and efficient AI operations.