“I pay £400/month and they’re shit”

Hey there! Chris here from Aeva AI receptionist for Healthcare.

This week, I met a practitioner who dropped a line that had me in stitches:

I couldn’t stop laughing when I heard this.
Partly because of how direct it was, but also because I’ve heard variations of this more times than I can count.

That got me thinking. Why do so many practitioners feel let down by these services?

Where exactly are the gaps in traditional receptionist call centres? And just as importantly, where do they still bring real value?

(I don’t think call centres are the enemy here. More on that in a minute.)

But before we dive into that, I want to share an exciting story from one of our new customers, and the buzz he felt in his first week using AI.

Ewen, one of our new practice owners based in London, jumped on a support call with me to ask a few questions about fine tuning his new AI receptionist.

Without any request, he launched straight into how impressed he was

“You’d think people would drop off when they realise they’re talking to AI,” he said.
“But they don’t.”

In just one week, several patients had already booked appointments through Aeva. One in particular stood out: a patient called with the intent to cancel. Instead of simply processing the cancellation, Aeva guided them to reschedule. Turning what would’ve been a lost booking into a saved one. Ewen said that’s the kind of interaction he doubts a human receptionist could’ve managed in the same way.

What surprised him most, though, was how well it worked in his rural clinic. He’d been hesitant about how patients in a more traditional area would respond to the tech, but the feedback and results have been nothing but positive.

No, and far from it.

Over 50% companies worldwide are now outsourcing their customer service to some extent, and a big share of that is handled by call centres or virtual receptionist services. These teams work because they’re built for volume and variety. One minute they’re answering for a solicitor’s office running on legacy systems, the next for a plumber using nothing but a shared calendar and a spreadsheet. It’s messy, but it works, because the people answering the calls are flexible enough to adapt on the fly.

The truth is, AI struggles in that level of chaos.

To build a high-performing AI receptionist for just one business takes time: understanding how bookings work, how cancellations are handled, which software is used, what terminology is specific. Now imagine doing that for thousands of different setups. It’s not just hard, it’s expensive and time consuming. Hugely so.

AI needs structure. It relies on APIs, consistent workflows, and repeatable logic. Humans don’t. A human receptionist can glance at a screen, follow an unexpected prompt, or adapt mid-conversation to something they’ve never seen before. That level of flexibility is still unmatched.

So no, I don’t think call centres are fading. In fact, in off-the-cuff or fragmented environments, they’re still the better option.

But here’s where the gap starts to close: when AI is deeply embedded in a specific ecosystem.

That’s where tools like Aeva fit in. It’s not trying to be everything for everyone. It’s built for healthcare, and more specifically, for practices using platforms like Cliniko. This narrow focus gives it a massive edge.

Because it understand exactly how those systems work. Every scenario has been accounted for. And AI is trained not just on “how to answer a phone call,” but on the full journey of a patient booking, from the first word to the final confirmation.

That level of depth is where traditional call centres begin to fall short. They can’t offer that kind of precision at scale, because they need to be generalists. Tools like Aeva get to go deep.

Beyond the obvious cost difference, (where AI receptionist services like Aeva are typically 50% to 80% cheaper) there are three key advantages that are often overlooked:

Human call centres juggle hundreds, sometimes thousands of businesses. It’s nearly impossible for a staff member to remember every little detail about your clinic. With AI, that memory problem disappears.

It absorbs your clinic’s information like a sponge. For Aeva as an example, you can easily preload over 150 tailored Q&As into its knowledge base to recall instantly, every time.

We’re all human. Some days are better than others. Different agents pick up the phone, and every one handles a call slightly differently. Different tones, styles, even accents. That inconsistency adds up.

With AI, your receptionist doesn’t change. It handles calls your way, every single time. Trained specifically for your clinic, it sticks to your workflows, your preferences, and your tone of voice. There’s no “off day.”

Call centres work on templates. With one person answering for dozens of businesses, there’s only so much personalisation possible before it becomes unmanageable.

AI is the opposite. Every question, every phrase, every call flow is built for your clinic alone. Want it to greet new patients differently? Route urgent cases another way? Ask follow-up questions only when needed? Almost anything is possible and it’s all controllable through your computer.

Lately, I’ve been having a lot of conversations with clinics. Listening to how reception actually works day to day. Where things flow, and where they don’t.

One thing is clear: it’s not about whether AI is better than a call centre. It’s about how well the tool fits the way your clinic already works.

If there’s a solution that’s been purpose-built for the exact systems and workflows you use, it’s almost always going to outperform a one-size-fits-all service. Not because it’s smarter in theory, but because it’s been designed with your reality in mind.

Call centres still make sense for clinics with more complexity, or where the software stack doesn’t support any level of integration. But if the setup is there and the right tools exist, it’s worth thinking carefully about whether generalist support is holding you back more than helping.

As always. Keep innovating.

Chris Baxter

co-founder, Aeva AI Receptionist for healthcare

www.aevaai.com

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