Which approach best describes event-driven data processing in CX/AI architectures?

• A. Requires no security controls.
• B. Process data once per day in batch.
• C. Process data in response to events as they occur.
• D. Avoids real-time processing.

Answer: (C)

Event-driven processing is about taking action as soon as something happens. In CX/AI architectures, events are things like a customer message, a page view, a chat sentiment shift, or a completed transaction. When such an event occurs, the system triggers processing right away, often enabling real-time or near-real-time insights and responses. This makes it possible to personalize experiences, route interactions to the right channel, or surface alerts the moment they’re needed.

That’s why the best description here is processing data in response to events as they occur. It captures the reactive, low-latency nature of event-driven designs and aligns with how CX/AI use cases rely on timely decisions and actions.

The other statements don’t fit. Security controls are essential in any architecture, so claiming no security is needed isn’t accurate. Batch processing—handling data once per day—describes a different pattern that processes data after a delay, not in response to events as they happen. And implying it avoids real-time processing contradicts the core advantage of event-driven approaches, which aim for immediate or near-immediate processing and decisioning.