I had an issue with my nine-month-old ŌURA 4 Ring. The battery life had suddenly dropped from five days to two. Not what you want from a wearable that is supposed to fade into the background.
So I opened a help request in the app. Within seconds, an AI chat appeared. I will be honest, I did not have high hopes for how this was going to play out. I have been on the receiving end of enough "have you tried turning it off and on again?" exchanges to know how this usually ends.
I explained the problem. It immediately sent me an approval email to access diagnostics. A few minutes later it confirmed a fault, escalated to the support team, and asked me to confirm my contact details.
Then came the moment of delight. An email from Oura: "A replacement ring has already been shipped."
No lengthy back-and-forth. No proof requests. No "please provide more information" dance. No waiting for a human to validate that yes, my ring really was broken. Just seamless, intelligent service. Genuinely exceptional.
What was actually happening under the hood
Strip out the language, and what Oura had built was a service that took the customer's problem at face value and got out of its own way. The AI did not pretend to be a human. It asked permission to act, acted, and reported back. The escalation was not a hand-off into a black box — it came with a confirmed outcome.
Compare that with how most support flows work. You log a ticket. You translate your problem into the categories the system recognises. You wait. You get a holding response. You answer the same questions you have already answered. You wait again. Eventually something happens. Maybe.
The AI in this case removed several of those steps entirely. It captured intent in plain language. It pulled the diagnostic context. It triggered an action. It kept me informed. The friction the system normally creates was simply absent.
AI used with purpose
This is what I keep coming back to. The conversation about AI in service tends to default to "how many headcount can we replace?" — which is the wrong question, and the one that produces the worst implementations. The right question is the opposite. Where does the system currently waste the customer's time, and what can we remove?
For Oura, the answer was: the entire diagnostic conversation. The verification dance. The waiting. They did not replace people with AI. They replaced friction with AI, and let people focus on the parts of the experience that actually need a human — judgement, empathy, the tougher edge cases.
Every service organisation I work with has the same opportunity hidden in plain sight. There is a category of repeat work that does not need a human, never has, and is currently consuming the time of skilled people who could be doing more interesting work. AI used with purpose removes that work. Not the people. The work.
The bar has moved
The thing that surprised me most was not the technology. It was how quickly my expectations re-calibrated. Once you have experienced support that just works, every other support experience feels heavier than it should. The portal. The categories. The mandatory drop-down. The five days of nothing.
That is the bar now. Not because users are unreasonable, but because the rest of their digital life has moved on. The service organisations that thrive in the AI era will be the ones that recognise this and redesign around it — not the ones who add another chatbot to the bottom of the same broken process.
There is a lot every service organisation could learn from a battery that mysteriously dropped from five days to two.