The Shift in Customer Expectations
I found myself thinking about the small allowances people make for one another. A tired agent. A clumsy phrase. A moment when someone is clearly having a rough day. Most customers understand the human side of these slips.
AI does not receive that courtesy.
When a chatbot fails to grasp a simple question or a voice bot offers an odd tone, the reaction tends to be immediate. Trust recedes and the machine feels as if it has broken an unspoken pact. Cyara CEO Rishi Rana said that customers hold machines to a standard they would never apply to a human.
Why AI Feels Less Forgivable
I began to wonder why that gap exists. Rana suggested that people recognise human error through lived experience. We have seen it in shops, on phone calls, and in day-to-day life. When AI makes a mistake, the expectation of precision collapses and the experience feels disrupted. He states,
We are conditioned for human error. We are not conditioned for machine error
Modern consumer tools have reinforced this model of interaction. When a brand system falls short, customers feel the difference almost immediately. Some cannot tell whether they are speaking to a person or a system. They still expect speed, accuracy, and consistency, and when these qualities drop, forgiveness tends to disappear. This reality is magnified as contact centers shift from scripted automation to autonomous agents that reason and act. This move to agentic AI holds extraordinary potential, but also heightened risks around accuracy, trust, and governance
Missteps and Their Business Impact
The consequences can be broader than a moment of irritation. A bot that uses the wrong tone can come across as rude. A slow agent assist prompt can intensify a tense conversation. An inaccurate answer can create compliance risks. Rana pointed out that these missteps often lead to escalations, abandoned journeys, agent strain, and a gradual erosion of trust that becomes visible later in churn or survey scores.
In regulated industries, the impact can extend further.
Why Assurance Matters
This brings the conversation to assurance. Traditional testing checks predictable paths. Agentic AI does not behave in predictable ways. Responses shift. Tone varies. Journeys can go an infinite number of ways. Rana believes,
It’s not a technology problem, it’s a validation problem: organizations are investing heavily in automation and AI, but their testing approach has to evolve, too. You can’t use manual spot-checks to validate autonomous systems that operate 24/7
Risk based assurance examines accuracy, sentiment, safety, and consistency across channels. It identifies hallucinations, outdated knowledge, tone fluctuations, and cross channel drift before customers encounter them. It supports both brand protection and customer protection.
The Pace of Deployment and the Risks It Creates
Speed is shaping decisions. Teams are encouraged to ship new AI features quickly. Rana warned that cutting corners or relying on manual checks increases the likelihood of failure, particularly as systems move from pre-determined paths to dynamic, unpredictable ones. Only AI-powered assurance can create and maintain an adequate number of test cases, understand customer intent, hand calls off to human agents when warranted, and confirm customer goals are actually reached.
When companies assume issues can be fixed after launch, the trust may already be damaged.
Rebuilding Trust After an AI Failure
I asked whether broken trust can be repaired. Rana said it can, although slowly. Customers remember poor AI interactions, and 67% of them will walk away from a brand after just one bad experience, Rana said. When a bot wastes time or provides incorrect guidance, the memory lingers.
Brands can regain trust by fixing root causes, communicating improvements clearly, and using continuous assurance to prevent new issues. Trust returns one interaction at a time.
The New Reality for AI in CX
The larger shift is that AI has raised customer expectations. People compare brand systems with the best tools they use every day. Hope and manual checks are no longer suitable. Accuracy, tone, and safety must be built in from the start.
People forgive people. They tend to judge machines more quickly. In the age of generative and now agentic AI, the first impression can be the only chance to earn confidence.
Connect With Cyara
If you want to explore how to strengthen AI reliability and protect customer trust across your contact center, you can connect with Cyara for expert guidance and a closer look at modern assurance capabilities.
