AI governance and accuracy challenges in enterprise operations

Enterprises are facing challenges in managing Artificial Intelligence (AI) within customer experience (CX) operations and data workflows. Current governance often focuses too narrowly on technical aspects like models and data, whereas effective governance must integrate customer context, human-AI workflows, and accountability to mitigate reputational and regulatory risks.

Furthermore, AI agents frequently produce inaccurate or risky outcomes when they lack specific enterprise context. Research indicates that agents operating against live enterprise data without a context layer achieve only approximately 65% accuracy, as they tend to invent answers when they encounter unknown terms or metrics. Implementing a context layer, such as an AI gateway, can significantly improve accuracy to over 98% by providing the necessary institutional knowledge and definitions.