# Your Next Doctor’s Visit Might Not Feel Like One > Source: > Published: 2026-09-03 03:27:13+00:00 Quick, think back to your last doctor’s visit. You probably spent more time getting *to* it than actually *in* it. Booking an appointment through one portal. Logging into a different app to fill out intake questions. Re-typing your medication list for the tenth time because that app doesn’t talk to the last one. Then finally, eleven rushed minutes with someone who spent four of them re-reading what you just typed, because none of it made it into the system they’re actually looking at. Here’s the thing nobody says out loud: **the appointment was never really the point.** The doctor’s judgment was the point. Everything else, the scheduling, the waiting, the fixed time slot, was just the clunky container it came in, because there was no better way to deliver it. Here’s the real shift happening right now: **most of the time, a doctor doesn’t need to see you live. They need enough good information to make a call.** AI’s job is to gather that information, completely and fast. The doctor’s job is still to make the call, just not necessarily live, and not necessarily *your* usual doctor. Whoever’s free next. **In one line:** AI collects your full picture and lines it up. The first available, qualified doctor reviews it and decides, confirm the plan, order more tests, or bring you in. Anything that sounds like an emergency skips the line completely and gets a real person, immediately. Back in 2020, video visits went from “weird and rare” to “everyone’s doing it” almost overnight. Then, once clinics reopened, a lot of people quietly went back to sitting in waiting rooms. Here’s why that happened: **early telehealth didn’t actually remove the bottleneck. It just moved it onto a screen.** You still needed a scheduled time slot. You still waited weeks for an opening. You still got fifteen live minutes with one specific person. The room disappeared, but the waiting didn’t. The real fix isn’t a better video call. It’s realizing that **most visits don’t need to be live at all.** They need to be *reviewed*, by a real, qualified person, as soon as one is free. That’s a queue, not an appointment. And a queue can move a lot faster than a calendar. This phrase gets thrown around loosely, so let’s make it concrete. In this model, it means: Simple rule: nothing meaningful ships without a real doctor’s sign-off. The only thing that changes is whether that sign-off happens live or async. Here’s what it looks like from your side, step by step. No static form. You talk or type, and the AI keeps asking smart follow-ups, the way a good triage nurse would: *When did this start? Does anything make it better or worse? Any fever?* It already has your history, so you’re not repeating your medication list for the ninth time. It keeps going until it has a genuinely complete picture, not just enough to check a box. This is the fork in the road, and it’s the most important step in the whole system. Instead of waiting three weeks for *your* doctor’s next opening, your complete case file, symptoms, history, AI’s initial read, drops into a shared queue. Any qualified, available physician in the network can pick it up the moment they have a few minutes. You might hear back in twenty minutes. You might hear back that evening. Either way, it’s usually faster than the old appointment system, because you’re not waiting on one specific person’s calendar. The doctor reads the full case, not a rushed six-minute conversation, an already-organized summary, and decides. They can: Either way, a licensed human made the decision. The AI just did the legwork to get them there faster. The plan, the reasoning, and any next steps land in your record. If it’s ongoing, follow-up monitoring keeps watching in the background and flags a human the moment something changes. The old model had one doctor, one patient, one scheduled slot, no matter how simple or complex the issue was. That’s an expensive way to allocate a scarce resource. The queue model breaks that. A doctor can review five or ten well-organized async cases in the time it used to take to run two live appointments, because the AI already did the interviewing and organizing. Patients stop waiting three weeks for things that take five minutes of a doctor’s actual attention. And genuinely urgent cases don’t get stuck behind routine ones, because they never enter the queue in the first place. That’s a real efficiency gain across the whole chain, patients, doctors, hospitals, and eventually the people paying for all of it. What that pressure actually does to cost and insurance is a big enough question that it deserves its own piece. But the shape of it is intuitive: when something gets meaningfully faster and cheaper to deliver, the price eventually has to answer for it. Every horror story about “AI healthcare gone wrong” comes from putting the human in the wrong spot, or skipping them entirely. A few lines that need to stay solid: **Nothing skips the queue except real emergencies.** The urgency check has to be genuinely conservative. When in doubt, it should route to a live human, not the queue. **Every plan still needs a real doctor’s signature, live or async.** The AI can prepare the case and suggest a direction. It cannot be the final word on a diagnosis, a prescription, or a treatment plan. Ever. **“Next in the queue” can’t quietly become “ignored.”** If cases sit for hours with no clear expectation of when they’ll be reviewed, patients will lose trust fast. There has to be a visible, honest promise: *you’ll hear from a doctor by X.* **A confident AI suggestion is still just a suggestion.** When a doctor sees a clean, pre-written recommendation, there’s a real pull to just approve it without a second look. That’s human nature, not laziness. The fix is in the design: show the doctor the AI’s uncertainty, not just its conclusion, and make disagreeing effortless. **Speed for most can’t mean worse for some.** This model is a massive win for anyone with a common, non-urgent issue. It has to be built so it doesn’t quietly fail people with limited internet access, limited English, or symptoms that are hard to describe in text. There should always be an easy “just connect me to a person now” option. The biggest mental shift here isn’t “AI talks to patients now.” It’s that **your care is no longer tied to one doctor’s calendar.** It’s tied to a pool of qualified doctors and a well-organized queue. Speed doesn’t come from any single doctor working faster, it comes from matching the right available doctor to the right case, instantly, at scale. Most telehealth today already lets you skip waiting for “your” doctor and get matched to the next available one — but it’s still built around a live call: you wait, then you talk to someone in real time. This is different. The AI conversation happens in real time, on your end. The physician’s review happens completely asynchronously, on theirs, no call, no live back-and-forth, just a complete case file they can pick up whenever they have a few free minutes. That’s closer to how a specialist reviews an e-consult, or how a claim gets adjudicated, than to a faster video-call queue. The waiting room isn’t turning into a video call. **It’s turning into a queue, one that moves fast, because AI does the interviewing and a real doctor still makes every real decision.** Urgent stuff still gets a live human, instantly, no exceptions. Everything else gets reviewed properly, just without making you wait for one specific calendar to have an opening. Getting that balance right, fast where it’s safe to be fast, human wherever it actually matters, is the whole job. Done well, you won’t think about the system at all. You’ll just get an answer, from a real doctor, faster than you used to. *I’m a staff engineer with 13+ years building software in the healthcare space.* [Your Next Doctor’s Visit Might Not Feel Like One](https://pub.towardsai.net/your-next-doctors-visit-might-not-feel-like-one-3e1c8b0f33fe) was originally published in [Towards AI](https://pub.towardsai.net) on Medium, where people are continuing the conversation by highlighting and responding to this story.