AI vs. Humans in Customer Service? You’re Asking the Wrong Question

I clicked the support button on my health insurer’s website. It replied with a list of six or seven possible reasons for my call, none of which matched the actual reason. I typed “human” in the input field, and it repeated the same list. Does this sound familiar? That wasn’t an AI problem. In fact, it probably wasn’t even AI, but that doesn’t matter. It was a design problem that caused a bad customer service experience.

Everyone seems to assume that AI will magically fix customer service. It won’t. AI is a tool. A powerful one, yes, but still just a tool. Tools don’t improve customer service. Systems do. And more importantly, the thinking behind those systems does.

What I experienced wasn’t cutting-edge automation. It was a rigid system that didn’t account for real-world variation. It didn’t listen. It didn’t adapt. And it certainly didn’t make it easy for me to solve my problem.

But let’s not let humans off the hook.

A Human Customer Service Experience

We’ve all dealt with support people who don’t listen, who stick to a script even when it clearly doesn’t apply, or who pass the issue along without taking ownership. You explain your problem, they respond with something unrelated, and suddenly you’re stuck in a loop that feels just as frustrating as that chatbot.

Here’s the uncomfortable truth: bad customer service isn’t caused by AI or by bad support reps. It’s caused by poorly designed systems. And humans are the ones who designed those systems.

And the common failure point is complexity and rigidity.

It’s About Solving the Problem for the Customer

Customers don’t want to figure out your system. They want their problem solved.

More and more, people don’t care whether they’re interacting with a person or a machine. They care about three things:
Is it easy?
Is it clear?
Does it work?

If the answer to any of those is no, you’ve got a problem.

This is where organizations miss the mark. Systems are often designed around internal efficiency instead of customer usability. The result is predictable: confusing workflows, unnecessary steps, and interactions that feel disconnected from the actual issue.

Here’s the part that matters most: humans are responsible for all of it.

Humans Are Responsible for the Customer Service Experience (Whether it’s with a Human or a Machine)

Humans design the AI systems. Humans design the support processes. Humans decide what options appear in that menu and how flexible the system will be. If the experience is frustrating, it’s because someone designed it that way, whether intentionally or not.

That also means the solution is in human hands.

I often wonder whether the person who designed a system ever actually used it.

Even machine-based systems need to operate with empathy and compassion for the human they’re serving. That doesn’t mean a chatbot needs to sound emotional or overly friendly. It means it needs to recognize intent, allow for variation, and make it easy for someone to get unstuck.

Empathy in a system looks like flexibility. It looks like clear paths forward. It looks like giving the customer a way out when the system isn’t working.

It definitely doesn’t look like a machine using empathetic words and phrases, while still being difficult to use.

Good customer service, whether delivered by a person or powered by AI, comes down to simplicity and focus.

Make it easy for customers to explain their issue. Make it easy for them to get help. Make it easy for the person or system helping them to understand context and take action.

It’s About Intentional Design

That requires intentional design. It requires stepping back and asking, “If I were the customer, would this make sense?”

It also requires accountability. Someone needs to own the outcome, not just the interaction.

Because here’s the bottom line.

When I typed “human” and got the same useless list back, the system failed. Not because it was a machine, but because it was rigid, poorly designed, and disconnected from what I actually needed.

Your customers don’t care how advanced your technology is. They care that you solved their problem and how easy you were to work with.

Frankly, your job is to make it easy for them to solve their problem, whether that happens with human help or machine help.

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