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 Vice President of Value Consulting, Clayton Lougeé 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. Lougeé 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. Lougeé 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. Lougeé 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.