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If you’re working in a healthcare contact centre today, you already know the pressure points: patients waiting too long to speak to the right person, frontline staff burning out under endless queues, and leadership struggling to hit national KPIs. It’s a system stretched to its limits — and everyone feels it.
Working with NHS providers and smaller healthcare organisations across the UK for many years, I’ve seen this play out up close. Whether it’s a local clinic or a national service like 111, the challenges are strikingly similar. On the other hand, I’ve also seen how, when used thoughtfully and implemented in the right way, AI can start to change the narrative – not as a hot tech trend, but as a genuine support system for both patients and staff.
In this article, I’ll show you where AI can make the biggest impact in the patient experience, how to avoid common pitfalls, and what practical, affordable steps you can take to get started — without losing the human touch that healthcare is built on.
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What This Blog Covers:
- The Patient Journey Is Broken — And Staff Are Bearing the Brunt
- AI as an Assistant, Not a Replacement
- Affordable Wins: Small Tools, Big Returns
- Why Hyper-Personalisation Needs Careful Handling
- Rolling Out AI the Right Way
The Patient Journey Is Broken — And Staff Are Bearing the Brunt
Let’s kick things off with a bit of a hard truth: the current system isn’t working – especially for patients. Despite the leaps and bounds the tech space has made in recent years, today, the average patient journey is often marked by two things: long wait times and misdirected calls. Imagine being in distress, finally getting help after waiting for what feels like a lifetime, and then hearing, “Sorry, I can’t assist you with that”, or “Let me connect you to another department”.
Not only is that incredibly frustrating for the patient, but it also overwhelms frontline staff who feel helpless and ineffective. When call handlers are fielding irrelevant queries or rushing through notes and skipping important steps, paired with a growing queue behind them, the ripple effect is poor service, missed KPIs, and a burnt out team. And as you might’ve guessed, that bedside manner that is crucial to optimal healthcare swiftly gets pushed to the bottom of their mounting priorities.
But this is exactly where AI can step in: not to replace people, but to empower them.
AI as an Assistant, Not a Replacement
The widely held belief that AI will replace humans is a common fear — and understandably so. If you’re a manager considering implementing AI in your organisation, you might be thinking something along the lines of: ‘Seeing as AI is so great at so much, what’s the point of having agents in the first place?’ These are the kinds of questions I get all the time, and here’s what I always say in response: AI should assist, not replace.
The most successful implementations we’ve seen are where AI takes the pressure off staff by handling the admin-heavy and repetitive tasks. Let’s have a quick chat about what this looks like in practice:
Real-Time Transcription and Summarisation
For example, take wrap time: the two to three minutes agents take to write up patient notes can be automated by AI through real-time transcription and summarisation. On its own, those few minutes might be a drop in the ocean of working hours. But think about the time saved per call, per agent, multiplied across a contact centre. That in itself frees agents to focus on what matters most: patient care.
AI-Driven Quality Assurance
We’ve also seen brilliant results from AI-driven quality assurance tools. Instead of manually listening to hours of calls, AI tools can score calls on key metrics like whether the agent introduced themselves correctly, offered reassurance, or met key compliance points. They can even detect sentiment, identifying when a patient feels anxious, frustrated, or reassured. If that isn’t powerful enough, these tools can also flag training opportunities – which goes beyond just assisting, but empowering your agents as well.
Affordable Wins: Small Tools, Big Returns
Those are just two examples that individually can have a huge impact on agent performance and productivity. So, as you can see, AI doesn’t have to be a major investment to be effective. One of the most cost-effective tools we’ve implemented for one of our customers is a postcode checker in a dental 111 service.
Here’s what it does: if a caller is from outside the service area, the AI identifies that from their postcode and politely tells them they’re not eligible — before they waste time waiting. That tool alone cut inbound calls by 33%! Just think about how many unnecessary calls that saved for staff — and how much frustration it avoided for patients. Not only that, but this is the kind of data you can bring to your leadership team to show value.
On that note, this isn’t about jumping on the AI bandwagon, but making sure you define your KPIs early so you know if the tool is working. Whether you're measuring reduced queue times, call accuracy, patient satisfaction, or staff workload, define exactly what you’re looking to get out of this solution upfront. Without these clear goals and targets, you’ll just be assuming that AI is improving operations.
Why Hyper-Personalisation Needs Careful Handling
As I’ve been sprinkling in throughout this article, AI will never replace agents. Human agents lie at the heart of excellent patient experience. However, something I hear a lot about is AI-powered hyper-personalisation. In other words, using AI to tailor services based on a patient's history. I know it sounds clever, but it can seriously backfire.
Let’s say, a caller (we’ll call her Marie) previously rang in about a mental health issue. Today, she’s calling in about a cold. Herein lies the problem: if AI auto-routes her based on historical data alone (which hyper-personalisation does), she may end up in the wrong department, facing yet another frustrating delay. Taking your call centre back to square one even though you’ve invested in this technology.
This kind of profiling — while well-intentioned — can really go wrong without proper checks in place. Hyper-personalisation works only when it’s guided by clean, relevant data and contextual understanding — not just past behaviour or a patent’s history. It’s a classic example of why we need to start small, test thoroughly, and always validate what AI suggests before going all-in.
Rolling Out AI the Right Way
Now that we’re pretty much clear on how AI can impact patient experience, let’s unpack the best ways to roll this tech out and what common pitfalls you should avoid.
Getting Buy-In from Your Teams (and Keeping It)
One of the biggest mistakes I see businesses make is rolling out AI without involving their agents. While leadership makes the decisions, it’s the people on the ground that need to buy in as well because they’re the ones using it. I’ve seen this all too often: management suddenly decides to implement a certain tool overnight, which leaves agents asking: “Is this replacing me?” or “How do I even use this?”.
That’s exactly what you don’t want to happen, because it’s a guaranteed way to fail. Here’s what to do instead:
- Be transparent: Communicate early and clearly about what the AI does — and more importantly, what it doesn’t do.
- Train properly: Don’t assume people will “just get it.” Walk them through the tool, show them what’s in it for them.
- Position AI as a tool for empowerment, not control: A little hesitance in the beginning is normal, but the main point is that AI is here to help them. It’s not what you say, but how you say it after all.
Make Sure Your Data Is Ready
You’ve probably heard this a million times (especially if you’ve read some of our other articles), but it always bears repeating: AI is only as good as the data you feed it. I’ve seen organisations excited to implement tools like Microsoft Copilot, but their data is scattered or unstructured. That’s a recipe for disaster.
More specifically, compliance, data governance, and data hygiene aren’t just NHS buzzwords — they're non-negotiables. The bottom line is that if you don’t know what you want to get out of AI, or can’t measure its impact (both of which require a solid understanding of the state and location of your data), you’ll quickly find yourself underwhelmed and over budget – or worse, in the middle of a compliance breach.
Check out this blog, to learn how to run an effective data audit.
The Voice That Matters Is Still Human
At the end of the day, AI is cold and transactional (don’t let the human-like voiceover fool you, it’s still a machine). It doesn’t offer comfort, nor does it show empathy. We shouldn’t forget that healthcare is fundamentally human and that human touch must always stay front and centre.
That’s why I said AI is here to assist, not replace (because it really couldn’t). The best approach is to work in harmony: let AI handle the routine tasks like summarisation, routing, eligibility checks and form-filling. But let your people be the ones to connect. Whether the patient is in pain, feeling anxious, or just lonely, they need to hear another person on the other end of the line that can sympathise and relate to their experience – and can therefore, actually help.
Bridging the Gap Between Tech and Care
You don’t need to replace your entire system to see real, lasting change. Start with something small — like an AI tool that summarises calls or filters by postcode — and you’ll immediately feel the pressure ease off your staff, your systems, and most importantly, your patients.
But let’s not lose sight of why we’re even having this conversation. Right now, healthcare providers across the UK are battling long queues, burnt-out teams, and patient dissatisfaction that cripples businesses. If this is something you can relate to, know this: there’s a way forward, that balances tech with compassion.
Everything I’ve shared here comes straight from the frontline: working with NHS providers, 111 services, and smaller healthcare organisations just like yours for years. I can attest to the power of AI when it’s done right, and I’m here to help you get it right too.
These tools aren’t here to replace your people; they’re here to support them so they can do focus on what matters: providing care.
