Conversations sit at the heart of every customer interaction – but the ways customers want to communicate are evolving fast. Today’s consumers expect to engage with brands at any time, across multiple platforms, and they want those interactions to be meaningful, efficient, and aligned with their personal schedules and preferences.
Each customer contact is driven by intent. They bring a purpose, problem, need or question. Just as importantly, they bring expectations for how smoothly their issue will be addressed. The challenge for Align Technology and other organisations is: how to connect and respond to customers’ new and often unmet needs, so they can achieve their desired outcomes?
A new approach to customer conversations
Getting closer to customers and widening the circle of “customer obsession” requires a foundation of data. It’s only with access to the right information that we can personalise experiences, deliver relevant solutions, and effectively use advanced tools like AI and machine learning to meet rising expectations. This is where conversational AI becomes a key part of the strategy.
Conversational AI enables companies to grasp the context behind a conversation and respond in a way that feels natural and helpful. While there is still value in picking up the phone and talking to someone, conversational AI makes communication available 24/7, offering customers quick, consistent service at any time. What is more, conversational AI chatbots are constantly learning, improving language skills and understanding customer needs with every interaction.
Designing for the customer and the company
Of course, we’ve all encountered frustrating chatbot experiences – the ones that don’t provide answers or solutions and force us to escalate to a live agent. Often, these failures stem from designing the experience around internal processes, not the needs and preferences of the customer. That’s what we want to avoid at all costs.
To deliver value, a conversational AI solution must be built with empathy and customer intent in mind. This means enabling the organisation to give the right answer for each customer, making recommendations based on their preferences. An ideal experience offers an easy and natural self-service for common requests – like placing an order or asking about a product – while keeping the discussion succinct and avoiding unnecessary steps.
When implementing chatbots in highly regulated industries, like healthcare, where data privacy and security are top concerns, it’s critical to ensure privacy and regulatory compliance. Organisations need to have complete control over their data and the flexibility to enforce security, privacy and compliance policies. It’s also important that customers clearly understand they’re interacting with AI – not a person. This is particularly important, as research indicates that as AI becomes more human-like, it can be problematic, especially when people become confused whether they are talking to AI or a human. Ultimately, the experience for the customer needs to be quick and painless, while the chatbot reads between the lines to provide an empathetic and personalised interaction that makes the customer feel valued and heard.
Enabling human teams to add more value
Even as AI plays a growing role, customer service will always require human interaction. Conversational AI isn’t to replace people but rather to allow customer service teams to take on high-priority activities and deliver better service. With AI handling common tasks, service teams can focus their energy on more complex and valuable interactions, helping them be more strategic, personalised, and preemptive in their approach than ever before.
Customers value positive customer service encounters. In fact, over 80% of customers reported that receiving value during a service experience makes them more likely to repurchase, even when given a chance to switch to a competitor. Going one step further, we are beginning to explore how AI can transition from having a reactive function to a proactive one. Instead of waiting for a customer to reach out with a query or for issues to arise, companies can use predictive insights to anticipate needs and offer support before customers even realise they need it.
At Align, we are experimenting in this area and using AI to help us anticipate the needs of our customers to surprise them. For example, our doctors will regularly need to order replacement sleeves for their iTero intraoral scanners. By analysing data patterns, our customer service team can be proactive and helpful in their approach, reaching out to doctors and asking if they need to reorder before they run out. Here, AI is helping us to free capacity, and enable the team to spend more time on proactive, value creation activities. It’s a simple yet impactful way to create a more helpful experience.
The next era: proactive and predictive service
Customer-centric companies are reshaping service expectations by delivering personalisation alongside operational efficiency – and importantly, finding the right balance between the two. Conversational AI plays a critical role in enabling these advancements, giving customer service teams more space to listen, anticipate, and resolve issues before they happen.
This future-focused approach helps build trust and long-term loyalty with customers. When customers feel recognised and supported – not just in the moment, but before a problem arise – they’re more likely to return. At Align, our aim is to use AI to empower customer service teams to do just that: create meaningful, proactive interactions that drive a better, more satisfying experience.
