Traditional automation follows predefined rules and typically breaks when exceptions occur. AI agents can interpret documents, analyze data, adapt to changing inputs, and make context-aware decisions. This allows financial institutions to automate end-to-end workflows while maintaining greater accuracy, flexibility, and operational efficiency than rule-based systems.
