I found myself watching how comfortably people use tools like ChatGPT, Copilot, and Gemini. These systems have become quiet fixtures in daily routines. They write messages, tidy up documents, and answer questions with a level of fluency that once felt unusual.
Clayton Lougeé, Vice President of Value Consulting at Cyara, told me that customers now judge enterprise AI against these familiar experiences. When a service bot struggles to interpret natural language or offers an odd response, the gap feels obvious. That challenge is expanding rapidly amid the shift to agentic AI that does more than answer – it acts.
While generative AI waits for prompts. agentic AI pursues goals. Where generative AI responds to what you ask, agentic AI figures out how to solve your problem, and it takes action on its own. For contact centers, understanding this distinction is becoming essential as support moves from AI that answers to AI that resolves.
The Experience Gap Customers Notice
Consider the shift from asking Copilot to refine a paragraph to asking a retailer’s bot about to help make a return. The comparison happens instantly. Customers do not think about different models or architectures. They simply feel that one interaction works and the other does not. Lougeé points out,
Customers don’t think about models or architecture or assurance. They think: this brand does not get it
If an AI agent repeats itself, hallucinates information, or takes too long to reply, the customer’s confidence slides. Companies have started seeing higher contact volumes and longer handle times as people bypass automation and head straight for human agents.
Legacy Systems Under Pressure
Many CX leaders are aware that their platforms were built for a different era. Lougeé said that legacy systems cannot evolve quickly enough to meet modern expectations. Full replacement projects are expensive and risky, so brands look for ways to modernise carefully.
Assurance has become central to that effort. Every new AI component needs to be tested thoroughly before anyone outside the organisation interacts with it. Manual spot checks can no longer keep pace, especially for unpredictable agentic AI journeys with millions of potential conversation paths that make manual spot checks and rule-based testing obsolete.