Conversational AI creates text or voice interfaces that interpret requests, maintain relevant context, complete permitted tasks, and transfer appropriately to people.
Customer service, employee support, operations, and digital product teams responsible for conversational service channels.
Context retention and conversational data privacy
Frame the decision: Which user requests and channels the assistant should support
Prepare around this operating condition: Language, accent, terminology, and accessibility coverage
Build the capability in a bounded slice: Conversation, intent, persona, and fallback design
Validate with this evidence: Task resolution or correct handoff rate
Complete the stage with this usable output: Web, messaging, or voice assistant
Which user requests and channels the assistant should support
Conversation, intent, persona, and fallback design
Web, messaging, or voice assistant
Disclose that users are interacting with an automated assistant
Task resolution or correct handoff rate
The examples consider customer support triage and guided self-service, employee policy and process assistance, and appointment, enquiry, and service request handling; none is presented as client evidence.
Evaluation for customer support triage and guided self-service would examine task resolution or correct handoff rate while applying this control: Disclose that users are interacting with an automated assistant
Evaluation for employee policy and process assistance would examine answer accuracy and context retention while applying this control: Authenticate users before account-specific or sensitive actions
Evaluation for appointment, enquiry, and service request handling would examine fallback and recovery quality while applying this control: Provide visible handoff paths and preserve transfer context
Bring this decision to the conversation: Which user requests and channels the assistant should support A useful first output could be web, messaging, or voice assistant.