Australia has a customer service problem, and while AI is helping, it’s only part of the solution.
Over the past few years, we’ve seen organisations invest heavily in technology to improve the customer experience. In many ways, it’s working, AI is helping resolve issues faster, reducing wait times and easing pressure on customer service teams. But here’s the reality: despite all this progress, customer frustration remains high.
ServiceNow’s latest customer experience research shows Australians spent 113.5 million hours dealing with customer service issues in 2025. Despite the scale of the challenge, the results point to real progress. Australians now spend an average of 9.3 hours on hold, with AI removing around 10 million hours of waiting time. While there has been an improvement in wait times, nearly half of Australian customers say they would switch providers after a slow or poor interaction. That’s not a technology failure, it’s a process failure. Too often there is a disconnect between what a brand considers resolved and what a customer does. Even fast resolution can feel like a misstep to a customer when they’ve needed to call multiple times, repeat themselves to several customer service agents, navigate unclear policies, or struggle with tech to reach a human.
Faster isn’t always better
There’s no doubt AI has changed the game in customer service. Virtual agents can handle simple requests within an hour. Intelligent workflows mean issues are routed and resolved more quickly. Predictive tools can spot problems before customers even raise them. These are all wins. Customers expect speed and convenience as a baseline.
But complexity remains the real challenge. Our research shows 71% of customer service agents need to use four or more systems to resolve customer issues, and complex cases can take the equivalent of a full working week to close. When problems drag on, context is lost, empathy erodes, and customers still feel frustrated, regardless of how fast the first response was.
Traditional CX metrics like average handle time or call deflection focus on how quickly an organisation can close a case. They don’t tell us how the customer felt during that interaction. They don’t tell us whether trust was built or lost. You get an answer quickly, but it doesn’t quite solve your problem. Or you’re stuck going around in circles with a chatbot when what you really need is someone to listen and understand your situation. In those moments, efficiency feels cold. And repeated often enough, it drives customers away.
The moments that really matter
Not every customer interaction carries the same emotional weight. Checking an account balance or changing an address is usually straightforward. But issues like unexpected charges, service outages, insurance claims or delayed deliveries often come with stress, urgency or financial pressure. These are the moments that shape how customers remember an organisation.
Our research shows poor service experiences are a major driver of churn. If customers feel dismissed or trapped in an automated loop, frustration builds fast. If they feel heard and supported, even a difficult experience can strengthen loyalty.
This is where empathy becomes critical. Empathy in customer experience isn’t about being emotional. It’s about understanding context. It’s recognising when something is simple and when it’s not. It’s knowing when automation is helpful and when a human connection really matters.
AI should support empathy, not replace it
The real promise of AI in customer experience isn’t total automation. It’s intelligent orchestration. AI is excellent at handling routine tasks. But the goal shouldn’t be to automate every interaction. It should be to design experiences that combine the speed of AI with the judgement and understanding of people.
That starts with better intent recognition. Today’s AI can pick up signals in language, tone and behaviour that indicate urgency or frustration. When used well, this allows systems to identify when an interaction is becoming complex or emotionally charged.
The next step is escalation. Customers shouldn’t have to fight their way to a human. Clear, easy pathways to human support build confidence and trust, even if customers don’t always use them.
Just as important is continuity. Few things annoy customers more than having to repeat their story. AI should capture context and history, then pass it seamlessly to human agents. In this model, AI becomes an enabler of better human conversations, not a barrier.
Australians are clear about what they want from AI in customer service. Our research shows 58% see the biggest benefit of AI as 24/7 support, allowing them to resolve issues at a time that suits them. Nearly half say it has reduced errors and improved outcomes, and three‑quarters now prefer self-service as a starting point. However, whileAustralians value speed, convenience and round‑the‑clock access, 46% are concerned AI could come at the cost of human connection. The message is simple: Australians want AI to handle the simple tasks quickly, but not at the expense of empathy in moments that matter.
Rethinking how we measure success
If empathy matters, we need to change what we measure. Speed and cost will always be important, but they shouldn’t be the only indicators of success. More organisations are starting to look at metrics that reflect customer effort, sentiment and trust.
Some are using post‑interaction feedback to understand how supported customers felt, not just whether their issue was resolved. Others are linking CX data directly to churn, retention and lifetime value, making the commercial impact of good experiences clearer.
These measures need to apply to AI as much as to people. Virtual agents should be tested, trained and governed with the same care as human teams. If an AI interaction consistently leaves customers frustrated, that’s a signal to redesign it.
It’s also worth remembering the impact on employees. When AI takes care of repetitive tasks and provides better insights, frontline teams are more empowered to deliver empathetic service. That leads to higher engagement, lower burnout and better outcomes for customers.
Practical steps for CX leaders
So how do organisations close the empathy gap?
First, focus on the moments that matter most. Map customer journeys to identify interactions that carry high emotional or financial impact. These are the places where human support should be easy to access, with AI playing a supporting role behind the scenes.
Second, design escalation intentionally. Don’t treat human support as a last resort. Make it a visible, natural part of the experience so customers feel supported, not blocked.
Third, invest in continuous learning. Use insights from human interactions to improve AI models and give frontline teams real‑time information that helps them understand customer context and history.
Most importantly, keep asking a simple question: does this experience make customers feel understood?
The future of customer experience
AI is here to stay, and that’s a good thing. It has enormous potential to improve customer service, reduce friction and free teams to focus on higher‑value work.
But technology alone won’t fix customer experience. As AI becomes more common, it will stop being a differentiator for brands. Organisations that can preserve empathy without slowing service down by designing customer workflows where AI and humans work together, not in isolation, will see greater retention benefits.
Empathy isn’t the opposite of efficiency. When designed well, it strengthens it. Customers who feel understood stay longer, trust more and advocate more. In the end, success in AI‑driven customer experience won’t be defined by how fast we close cases. It will be defined by how well we put AI to work for people.