AI Agents sit at the core of the customer experience. They are the conversational layer through which customers ask questions, receive answers, and move through to a resolution. But as AI capabilities evolve, so does the way we architect what sits behind that experience.
https://www.zendesk.com/blog/zendesk-insights/expertise/stop-building-one-big-bot/
Customer interactions do not all follow the same route. Some requests can be handled and resolved by an AI Agent without a person getting involved. Others need a support agent from the outset, while some may begin with an AI Agent and need human attention later. The platform needs to support all of
Zendesk’s Resolution Platform is designed to do more than capture knowledge and procedures. It also provides the tools to manage and run actions across conversations, tickets and wider business processes. Action Flows provide the execution layer for that work. They can retrieve information, update
Zendesk AI Agents are more than just answer bots. They can understand what an end customer is trying to achieve and help carry the request through to a resolution. By combining knowledge, context, procedures and actions, they can interpret a policy, recognise the situation, decide what should happe
Customers do not experience support as a blank slate. They arrive with an identity, an order, a plan, a history, and an expectation that the company should know enough to help. When an AI Agent ignores that context, it asks people to repeat information, offers options that do not apply to them, or f