The Phone Tree
I called a large government agency last year. The website told me to call. The letter they mailed me told me to call. It was the number for my exact question, printed in bold.
Twenty minutes on that call. Never put on hold. Never spoke to a human being. Instead I navigated a system that wanted me to press 1, press 2, enter my Social Security number, confirm my address, press 3 for more options, listen to another menu, press 1 again, enter information I'd already given. Every step felt like progress. Every step was just another layer of the same loop.
At the end of twenty minutes, the system told me it couldn't help me. Not that I'd reached the wrong department. Not that I needed to call a different number. Just that it was unable to process my request. The same request the website and the letter said this number existed to handle.
Nobody designed that experience around the caller. They designed it because it's cheaper than a solution that meets the customer's need. The system was built to sort and deflect, not to help. Every person who calls that number walks away with the same conclusion: this agency does not want to talk to me.
The Call
A few weeks later I called the Snohomish County non-emergency line. I've called that number plenty of times for work. I know what to expect: a harried, overworked 911 operator who happens not to be on an emergency call at that moment. I give them the basics, they file the report, I move on.
An AI answered. Her name is Ava.
My immediate reaction was anger. Not mild annoyance. Genuine frustration. I'm calling the police, and I get a machine? After twenty years of phone trees that exist to keep you away from help, I knew exactly what was coming. I was already rehearsing my "agent, agent, agent" mantra to bypass it.
Then Ava asked me to explain why I was calling. Not from a menu. Not "press 1 for theft." Just: tell me what's going on.
So I did. And the response was natural. It came back at the speed of the conversation, no awkward pauses, no loading a script. She listened to what I said, understood the situation, asked relevant follow-up questions. She filed the report, gave me a case number, and told me a deputy would follow up if there were questions.
I've called since. When Ava determines a non-emergency call is actually urgent, she transfers the caller immediately to a human dispatcher with full context. She knows the difference. Since launching in 2024, the system has handled over 220,000 non-emergency calls and reduced the load on dispatchers by 90% during peak hours. The overworked operators I used to reach are still there. They're just handling the calls that actually need them.
Why One Worked
My frustration with the government phone tree and my initial anger at a bot picking up the police line came from the same place. I expected to be handled, not helped. That is the instinct a customer brings to their first encounter with AI in any business.
The sheriff's system won me over because it was designed around what the caller actually needs. The government phone tree was built around the organization's budget. One system was geared toward the customer. The other was designed to make the customer go away.
That is the difference between technology deployed well and technology deployed strictly to create efficiency. Same underlying tools. Completely different experience for the person on the other end.
The Cost of Getting It Wrong
AI is in its early trust-building window right now. A customer arriving at a new system carries twenty years of bad phone trees with them. Every chatbot that couldn't answer the question. Every "your call is important to us" on a forty-five minute hold. Every automated system that made a simple task harder. They are not starting from a place of trust. They are starting from "great, another machine that can't help me."
The first time a customer encounters AI in a business, they form an opinion that is hard to reverse. A system that fumbles the interaction, gives canned answers, or makes the customer feel like a line item instead of a person does real damage. Not just to that interaction. To their willingness to come back.
A system designed around the customer's actual experience, one that handles the right tasks at the right pace and knows when to hand off to a human, builds the kind of trust that turns a skeptic into a regular. That is the system worth building. The other kind is not just wasted money. It is a step backward.
The Question That Comes First
The difference between the phone tree and Ava was not the technology. It was whether anyone asked the right question before building it.
That question, the one worth bringing to every vendor meeting and every scoping conversation, is this: does your customer feel that your technology is working as hard as you are to value them and their time?
That is where every good system starts. The technology is the easy part. The choice to build around the person who is going to use it is what makes the difference between a system customers thank you for and one they warn their friends about.