How can we improve customer service with AI?

That’s what we all want to know, isn’t it?

As AI has improved, so have the opportunities for better customer service. Sure, call summaries, automated notetaking and routing enquiries are amazing time-savers, but they’re only scratching the surface.

Where AI really comes into its own is helping customers solve the problems they think should be simple (but quite often aren’t!), like changing an appointment, updating an insurance policy, or tracking down a missing delivery.

Behind the scenes, those requests need information from multiple systems and teams, making them slow and frustrating to resolve. AI can pull those pieces together in seconds, helping customers achieve what they need faster, while giving human agents the context they need to step in when it matters.

But what does better customer service look like?

The easiest way to understand great customer service with AI is to think about the situations that may make a customer get in touch, and to resolve these before they have to!

The examples below aren’t futuristic use cases. They’re everyday customer service interactions where AI reduces effort for customers and quickly provides the right response.

“I can’t make any of these appointments, and I’m nearly out of my meds!”
Getting a GP appointment feels a bit like Mission Impossible at the moment, doesn’t it? And if a patient has been offered times that don’t work for them, the next step normally involves them joining a massive phone queue or waiting (and hoping!) for a receptionist to call them back. AI can recognise that the problem isn’t just booking an appointment, but a medication concern. It can search for alternative appointments, flag the urgency to the practice team, and make sure the right information reaches the right people, without the patient having to repeat themselves.

“Hm that’s odd. It says delivered, but I haven’t received it.”
Urgh! Been there. But instead of sending the customer around in circles, AI can check delivery evidence, identify whether the parcel was left somewhere safe, investigate the delivery status and guide the customer to the correct next step. Whether they need to raise a claim, contact the courier, or arrange a replacement, they can quickly get updated about where their delivery is.

“Omg there’s water coming through my ceiling, but no one’s available until next Thursday!”
When the roof’s (literally) about to come down, customers don’t want to be left waiting for help. Instead of treating every repair request equally, AI can recognise keywords that indicate an emergency, provide approved safety guidance immediately, and escalate the job to an emergency repairs team. Phew.

“They can’t install my broadband until two weeks after I move, but I work from home! What am I going to do?”
Waiting a fortnight after your house move for your broadband to be switched on just doesn’t cut it these days. Instead, AI can check for earlier installation slots or look for temporary connectivity options. That means a happier customer, and no need for them to contact multiple departments.

Sounds great! How do we do that?

The question then becomes how we go about improving customer service and the broader customer experience (CX) with the help of AI.

Where does it hurt?
It starts with having a deep understanding of both your customer and your organisation. That means identifying where your customer journeys are currently breaking down and understanding why customers might be straying off the ‘right path’.

In doing so, you’ll find opportunities to remove some of the pain points that you’re facing, whether that’s unsustainable peaks in inbound traffic, low FCR rates, rising call handling times, or declining customer satisfaction, often driven by lengthy wait times and queries that aren’t resolved first time.

Understanding the reality of your current customer journey is one of the first parts of any successful AI roadmap (check out our handy guide). Step one is always knowing what you need to change.

Don’t get dazzled by the demos

Next, you need to think carefully about where AI can have the greatest impact and start identifying the right tools for the job. There’s a tonne of different AI tools out there, and it can be a little overwhelming when so many come with wonderful promises about how they’ll revolutionise your CX. Choosing the right tool for your organisation matters, because you’ll need software that can work alongside your existing systems, teams and data. And all of these need to be ready for AI.

According to MIT, some 95% of corporate initiatives ‘fail’, and often that’s because AI was deployed for AI’s sake, without the proper groundwork being done. In the words of Forbes, “Technology doesn’t fix misalignment. It amplifies it. Automating a flawed process only helps you do the wrong thing faster.”

So, take your time to get your ducks in a row, consult with the experts, and make sure the AI tools you choose won’t become more hassle than they’re worth. Nobody wants to spend budget on replacing the software they only just paid for!

Take it from the top

Getting it right is just as much about the people, and it starts at the top.

Senior leaders need to be proactive and deliberate in their approach to CX-AI. That could mean investing in new roles that provide the right technical expertise and management, or providing extra training to give employees the confidence to work alongside AI rather than fear it.

While this is the responsibility of the whole leadership group, having someone in the C-Suite act as the main driving force is important. That person can champion the organisation’s AI vision and provide clarity about the benefits, helping to keep momentum going throughout change.

Ignore your competitors

It also means listening to what your organisation’s data is really saying. No two customer journeys are the same, and just because a competitor has deployed a snazzy new AI Agent doesn’t mean it’s the right solution for improving your own customer service. For all you know, it could be one of those ill-fitting AI solutions that quickly ends up in the bin because it wasn’t properly thought through before deployment.

We say it a lot, but there is no “one size fits all” way to improve customer service with AI. What we do know is that the organisations seeing the biggest improvements aren’t necessarily the ones investing the most money, they’re the ones focused on using AI where it can make the biggest difference.

So, get the right foundations in place, choose AI that fits your business and your customers, and you’ll be in a much stronger position to deliver consistently better customer service.