Security and Compliance

A Voice AI Agent works with sensitive data: identity details, financial data and sometimes health information. Security is not a feature to be added later. It is a layer that has to exist from the start of the architecture.

Four questions to settle early:

1. Data sovereigntyWhere will the data be processed, inside the country or outside it? On-premise deployment answers this question at the root.
2. Access controlWhich AI Agent and which integration can reach which data? Roles and permissions should be defined for AI Agents with the same discipline applied to human employees.
3. AuditabilityWhen an audit request arrives, how quickly can you produce the trail of every decision the AI Agent made? Which data did it use, which system did it talk to, what was the outcome?
4. Human oversightWhich decisions can run fully automatically, which need approval, and which should never be automated?

That fourth question sits at the heart of enterprise AI governance. The phrase "human in the loop" is used often, but putting a person inside every decision is not good governance on its own. The real work is designing where the person needs to be. High confidence, low risk steps can run automatically. When uncertainty rises, or when a decision is critical for the customer, a person should step in.

CBOT's approach is built on regulatory compliance: the purpose of data processing is defined clearly, access is limited by role, and every interaction is recorded in an auditable way. Work towards enterprise security standards, SOC 2 among them, is managed as an extension of the same discipline.