Artificial Intelligence (AI) has been one of the most talked-about technologies in recent years. While tools like chatbots have been around for a while, interest in AI exploded with the arrival of ChatGPT in late 2022, sparking new conversations about how AI could change the way we work, communicate and serve our customers.
In customer service, AI is already starting to make a real impact. After years of hype, we’re seeing it move from theory to practice—helping contact centres respond faster, work smarter, and better meet the expectations of today’s customers.
However, it can be hard to separate the real opportunities from the noise. The terminology can feel technical, the technology itself can seem intimidating, and for many, it’s not always clear where to begin. In this guide, we’ll bring you back to the basics, cut through the noise, and help you get started on your AI journey.
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Customer expectations are rising. People want faster, more personalised support across a variety of channels, and they’re not afraid to switch providers if those expectations aren’t met. At the same time, contact centres are under pressure to do more with less, balancing rising service demands with tighter budgets and staffing challenges.
AI is stepping in to help contact centres navigate these challenges. With the ability to automate routine tasks, support agents in real time and provide insights that help teams work smarter, AI has the potential to significantly improve the way contact centres operate.
Here are some statistics that highlight the impact of AI:
At its core, artificial intelligence (AI) in customer service is about using smart technology to help your teams work more efficiently and provide better experiences for your customers. It’s not about replacing humans, but about giving them the right tools to do their jobs better.
Think of AI as an extra pair of hands that can work quietly in the background, answering simple questions, sorting through incoming queries, and even suggesting the best next steps during a live conversation.
Definition: Artificial Intelligence (AI). Artificial Intelligence (AI) refers to the simulation of human intelligence in machines. These systems are designed to think and learn like humans, handling tasks such as understanding language, recognising patterns, and making decisions. Artificial Intelligence in customer service is growing in popularity. From AI chatbots to virtual assistants, AI is transforming customer service by automating tasks, improving user experiences, and speeding up responses.
👉 Learn more about AI terminology in our AI glossary for customer service.
When we talk about AI in customer service, we’re usually talking about systems that can:
This is made possible by things like natural language processing (NLP), a type of AI that helps systems understand and respond to human language, and machine learning, which allows AI tools to get better over time based on data and feedback.
AI might sound complex, but chances are you’ve already used it, as a customer:
Behind the scenes, AI can also support contact centre agents by:
If you’ve been in customer service for any length of time, you’ll know that demands are only growing — more queries, across more channels, with higher expectations for speed, convenience and empathy. That’s where AI comes in.
For contact centres and customer service teams, AI isn’t just about keeping up, but about working smarter. It’s a way to improve experiences for customers and make life easier for the people supporting them.
Let’s break down how.
One of the biggest misconceptions about AI is that it’s designed to replace people. The truth is, AI works best when it works with your agents, taking care of manual tasks and repetitive workflows, freeing up time for agents and increasing efficiency. AI can support your team by:
It’s a bit like giving every agent their own personal assistant, one that never sleeps, doesn’t get overwhelmed, and gets better with time.
Customers want quick, simple answers, and they don’t want to repeat themselves. AI can help you deliver on those expectations without putting more pressure on your team. Here are some of the main benefits:
All of this can translate to better customer satisfaction, improved CSAT/NPS scores, and more efficient operations.
Now that we’ve looked at what AI is and why it’s becoming more relevant in customer service, you might be wondering what it actually looks like in practice— and where to begin.
The truth is, you don’t need to have everything figured out to start exploring AI. Many contact centres begin with small, manageable use cases that solve specific challenges. Whether it’s easing the pressure on your team during busy periods or giving customers quicker answers to simple questions, the right tools can make a real difference early on.
These tools are often the first step into AI for many contact centres. They’re designed to be simple to implement and easy to use, without needing deep technical knowledge.
Basic chatbots: These are AI-powered virtual agents that sit on your website or in your app and answer simple, repetitive questions, like “Where’s my order?”, “How do I log in?”, or “What are your opening hours?”
They work by understanding the intent behind the customer’s message and matching it to a relevant response. Unlike traditional bots, they don’t rely on exact keyword matches, they use natural language processing to understand everyday language.
AI-enhanced IVR (voicebot): With AI, your IVR can become more intuitive. Instead of giving customers a list of numbered options, it can recognise what they’re saying and route them accordingly. For example: “I need to change my delivery address” → routed directly to the right team, without needing to press 1, then 3, then 5.
AI-assisted routing: AI can help sort incoming messages based on what they’re about, how urgent they are, or even the sentiment behind them. That means customers get through to the right person faster, and agents spend less time handling misdirected or duplicate queries.
Beyond the basics, here are some common ways AI is used to support both agents and customers:
Unlike traditional automation, which follows strict rule-based commands, AI can learn, adapt, and improve over time—leading to more natural, intuitive customer interactions.
Here are a few ways organisations are using AI today.
Housing and membership bodies
Chatbots handle common account or payment queries, helping reduce phone queues and freeing up time for more sensitive cases.
Retail and e-commerce
AI helps triage incoming queries, especially around delivery and returns, and supports agents with quick access to product or order information.
Utilities and telecoms
Voicebots guide callers more efficiently, while AI-powered assistants help agents find relevant information quickly during live interactions.
Healthcare and insurance
Virtual agents support patients or policyholders with basic information, while AI-assisted routing helps ensure more complex queries are handled by the right specialist.
Taking the first step with any new technology can feel daunting, especially when resources are tight and priorities are competing. The key is not to think of AI as one big transformation, but rather a series of small, manageable steps that add up to something meaningful. Assess whether AI is a good fit for your contact centre right now, and identify where to start.
Start by taking stock of your current challenges and goals. You might not need a full-blown strategy just yet, just a clear idea of the pressure points AI could help relieve.
Here are a few signs that AI might be worth exploring:
If any of that sounds familiar, even a small step with AI could help relieve some of the pressure, without needing to restructure your team or overhaul your tech stack.
To figure out where AI could make the biggest impact, it helps to ask a few practical questions:
These questions don’t need perfect answers, they’re simply a starting point to help you focus your efforts and find the right use case to begin with.
You don’t need to be an AI expert to get started, and you don’t have to do it all on your own. The right partner or vendor can help guide you through early decisions, suggest use cases, and make sure the solution fits your team’s needs.
Above all, be open to learning along the way. AI is evolving quickly, and so is customer behaviour. What matters most is having the curiosity to try new things and the flexibility to adapt when needed.
Once you’ve identified where AI could support your team, the next step is choosing the right solution, one that fits your current needs and helps you grow at your own pace.
There’s no shortage of tools out there, but if you’re just getting started, it’s important to find a platform that’s built with beginners in mind. That means avoiding unnecessary complexity and focusing on solutions that are easy to set up, easy to manage, and backed by the right support.
Here’s what to look out for — and the questions to ask — before you commit to anything.
Not all AI tools are created equal. Some are built for highly technical teams with in-house developers, while others are designed for customer service teams with little to no technical background. If you’re at the beginning of your AI journey, here are a few features that can make all the difference:
Like any change, it often comes with questions, hesitations, and a bit of resistance along the way. Whether you’re trying to secure stakeholder approval, reassure your agents, or build trust with customers, bringing everyone along on the journey is just as important as the technology itself. Let's look at some common barriers to AI adoption, and share some practical ways to overcome them.
1. Keeping the human touch
One of the biggest concerns around AI in customer service is the fear of losing that personal, human connection. According to our recent survey of 1,505 customer service professionals across Europe, this is the number one barrier to adoption.
And it’s easy to see why. Customers don’t want to feel like they’re talking to a machine — they want fast answers, yes, but also empathy and understanding when it counts. So, how do you make sure AI supports, rather than replaces, the human touch?
2. Managing change and overcoming resistance
Change isn’t always easy, especially when it feels uncertain. Whether it’s concerns about job security, unfamiliar technology, or fears of being replaced, resistance is a natural reaction. The best way to ease those concerns is with open communication and early involvement.
3. Addressing data and privacy concerns
When customer data is involved, trust is everything. It’s essential to show that your AI solutions are not only effective, but safe, secure and compliant. Here’s how to build confidence from the start:
4. Managing the cost of implementation
For many organisations, cost is a major consideration. And while AI doesn’t have to break the bank, it’s important to ensure the value is clear and measurable. To make the case internally:
Need help building a business case? Our Total Economic Impact™ Study revealed a 278% ROI for CX organisations using Puzzel.
When you’re just starting out with AI in your contact centre, a thoughtful, measured approach can go a long way. But like with any new tool or process, there are a few common missteps that can slow progress or impact results.
The good news? Most of these are easy to avoid with the right mindset and a bit of planning. Here, we’ll walk through some of the most common pitfalls we see in early-stage AI adoption — and how you can steer clear of them.
1. Rushing in without a clear goal
It can be tempting to try AI for the sake of it, especially with so much hype around the topic. But successful AI projects always start with a clear purpose.
Avoid this by:
Start with the challenge, not the technology, and let your business needs guide your approach.
2. Overcomplicating things too early
You don’t need to launch a fully automated, multi-channel AI solution on day one. In fact, trying to do too much, too soon is one of the quickest ways to overwhelm your team (and your customers).
Avoid this by:
Remember: you can always add more features later. Starting small gives you more control, more focus, and a better chance of early success.
3. Neglecting human input
AI can support your team — but it still needs people to guide, shape and refine it. When it’s treated as a “set-and-forget” tool, it rarely delivers the results you’re hoping for.
Avoid this by:
AI isn’t a finished product — it’s something you learn from and improve together.
4. Forgetting the customer perspective
It’s easy to focus on the internal benefits of AI (like cost savings or efficiency gains), but the customer experience should always come first.
Avoid this by:
Even the smartest AI won’t help if it creates friction for your customers.
5. Not measuring or iterating
If you’re not tracking how your AI is performing, it’s difficult to know what’s working, and what’s not. Even small adjustments can make a big difference, but only if you’re watching the right signals.
Avoid this by:
AI is a continuous improvement process, not a one-time project.
By now, you’ve explored what AI can do, how to get started, and how to avoid common pitfalls. If you’ve launched your first AI use case — or are even just planning one — that’s already a huge step forward. But what comes next?
AI adoption isn’t a one-time project. It’s a gradual journey, where each step builds on the last. Once you’ve seen early success and your team feels more confident, you might start looking at what else AI can support in your contact centre — and how to move from basic automation to smarter, more predictive tools.
Once the basics are in place, here are a few areas you might explore next:
Smarter triage and routing: Use AI to analyse incoming messages in real-time — factoring in sentiment, urgency, topic, and channel — to route customers to the best agent or resource.
Sentiment analysis and prioritisation: Spot frustration or urgency automatically, so your team can act quickly where it matters most.
AI-powered quality assurance: Automate parts of your QA process by using AI to review conversations for tone, compliance, or performance benchmarks — freeing up time for coaching and development.
Predictive analytics and forecasting: Leverage AI to anticipate contact volumes, identify emerging trends, or spot service issues before they escalate.
Personalised customer journeys: Use AI to tailor support experiences based on past behaviour, preferences, or previous interactions, improving satisfaction and loyalty.
These capabilities might sound advanced now, but with the right foundations in place, they become much more achievable.
You don’t need to move quickly. The most important thing is to grow in a way that makes sense for your team, your customers, and your wider goals. Here’s how to keep momentum going:
AI isn’t about doing everything at once. It’s about making thoughtful, incremental changes that help your team and customers alike. A single chatbot or routing assistant can make a noticeable difference and build momentum for bigger steps.
The key is to stay curious, stay practical, and involve your people at every stage. And remember: with the right support, AI doesn’t just help your contact centre run more efficiently, it helps it run more humanely, too.