In today's corporate landscape, the phrase many of us are faced with is, ‘We need to be doing more with AI.’ It's no surprise, with machine learning, automation and particularly, Generative AI, dominating headlines and reshaping digital strategies across every sector.
But here’s the uncomfortable truth: your customers don’t care about AI. They care about how you make them feel. They care about whether you make their lives easier. Above all, they care about an experience that just works.
Creating impactful customer experiences
We’ve entered an era where experience is everything. In our increasingly digital world, more of the everyday is automated, which is great when it works. We’ve all been there, when you’re trying to complete a simple task, only to get stuck in an unhelpful chatbot loop that turns a 5 minute job into a frustrating ordeal.
According to PwC, 73% of customers say experience is a key factor in their purchasing decisions - yet only 49% feel companies are delivering. It’s not about features or emerging tech, it’s about removing friction and delivering value quickly.
Customers aren’t impressed by your intelligent automation workflow. They’re impressed when their refund is processed in minutes. They don’t care how your chatbot is powered, but they do expect their question answered fast and correctly.
AI should be invisible and understated, but impactful.
AI’s role behind the scenes
Some of the most powerful AI use cases aren’t flashy. For example:
Real-time fraud detection by your bank. AI models analyse spending patterns and spot anomalies in milliseconds. Customers might just get a text asking, “Did you just make this transaction?” but behind the scenes is an advanced behavioural model protecting their money.
Real-time translation and accessibility. AI is helping public sector websites offer real-time language translation and screen reader optimisation, making services more inclusive without requiring manual updates for every language.
Predictive journey disruption alerts. AI models trained on historic and real-time data now predict delays and congestion and proactively notify commuters via apps, digital signage, or email. Commuters don’t care that it’s machine learning, they just know to take a different train and avoid being late.
These experiences matter because they work. The pitfall is when organisations lead with the technology, not the outcome. They deploy AI before asking whether the customer journey needs it, and the result is tools that create more frustration than value i.e. poorly trained chatbots, irrelevant recommendations, or service agents overwhelmed by noisy data.
Designing for humans
We’ve seen it across all sectors: when you start with real user needs, AI can become a powerful enabler, but it’s never the starting point. It isn’t about where can I use AI, but instead, here’s a problem and here’s the solution – can AI make it better?
Before AI is considered, you should start with:
Journey mapping: Where are the pain points?
Empathy interviews: What do customers actually need?
Service design: How can we make this feel effortless?
Once you’ve mapped the experience, then bring in AI to accelerate, personalise and optimise.
Experience is the differentiator
In a crowded market, products and prices can be matched, but the emotional connection, the ease of use and the sense that an organisation understands consumers needs is the real differentiator.
The best compliment a customer can give is “That was easy.”
If AI helps you get there, great. But if it doesn’t? No one will thank you for using it.
To summarise
AI is a powerful enabler, but it’s not a silver bullet. The goal isn’t to deploy the latest tech for the sake of it, but to enhance the experience in ways your customers notice and value.
While many providers can help you implement AI, only a few understand how to align it with real customer needs, operational realities and measurable outcomes.
That’s why the right partner matters. One that leads with customer challenges, not technology trends and brings a track record of using AI to optimise both its own services and those of its clients.
Before your next AI deployment, consider ‘will this make the experience better?’