How to Lead CX Through Rapid Change in 2026

As organizations turn more and more to the adoption of AI in Customer Experience (CX), we look to our 2025 Call Centre Helper Research to explore the rapid and far-reaching change it’s been having across the CX landscape.

We spoke with Steve Blood from Five9, sponsor of the CX portion of the research, to help interpret what the data is telling us, and what it means for organizations trying to balance innovation, efficiency and experience.

From Evolution to Revolution

When we met with Steve, the first thing he commented on was the speed and scale of change stemming from digital and AI channels.

“We’re at the point where this isn’t the gradual change of evolution – this is revolution.”

In fact, interactions are being reshaped so fundamentally that organizations are being forced to ask difficult strategic questions, particularly how far down the market AI-led customer service can realistically extend.

If businesses are betting heavily on AI, what is the smallest customer size they are prepared to serve, and how does that influence CX design?

Encouragingly, regardless of the ever-growing focus on AI, the research also shows that people still matter more than ever. Despite persistent narratives about AI replacing jobs, the data points to a growing belief in human and AI collaboration.

Rather than removing roles, AI is increasingly seen as a way to eliminate mundane work and elevate human contribution, provided employees are actively involved in shaping how that technology is designed and deployed.

Rethinking Feedback – From Surveys to Conversation

Another major shift highlighted in the survey is how organizations gather and interpret feedback. Traditional customer feedback mechanisms such as email and website surveys are declining – and that may not be a bad thing.

Customers are increasingly fatigued by prescriptive surveys that leave little room for genuine expression, often leading to low engagement and limited insight.

Survey data tends to capture extremes, portraying either the very good or the very bad experiences, while the nuances in between are easily lost. The research suggests it’s time for a rethink.

Encouragingly, there has been a significant increase in the use of speech and text analytics. This represents a move towards capturing the authentic voice of the customer, allowing us to hear what customers actually say in conversations, rather than how they respond to structured, often leading, questions.

Historically, this data was difficult to access and analyse, but modern analytics and generative AI have made it far more usable and scalable.

Used effectively, and with the right governance and observability, this insight can validate assumptions, uncover issues organizations hadn’t previously considered, and even be implemented into employee feedback and coaching. The potential here is significant, and still largely untapped.

Self-Service and Knowing When to Use It

When it comes to maximizing ROI from CX investment, self-service dominated the responses. Self-service offers clear, tangible cost savings, as reducing reliance on human agents makes ROI easy to calculate. Yet, this risks narrowing the CX conversation too much.

Research shows that 60–70% of consumers want to use self-service, but only on their terms. The disconnect arises when organizations design bots and self-service tools primarily around operational efficiency rather than customer needs.

When built for the business instead of the consumer, self-service can actively harm experience rather than enhance it.

Look at things from a customer’s perspective and deliver something that works for them.  ROI on self-service and CX improvement are sure to follow, leading to loyalty, retention and long-term value, which is where true value for money really lies.

When Is a Chatbot Detrimental?

Chatbots remain the technology many love to hate. While undeniably powerful, they too often struggle to match with what a customer really needs, and despite CX ranking as a top priority for a majority of organizations, this focus doesn’t always show up in how services are designed.

Chatbots are frequently built to save money rather than reflect the authentic voice of the customer.

As Vinay Parmar, Managing Director at Customer Whisperers Limited, puts it: “What we need is a shift from this efficiency-first mindset to a more experience-driven approach.”

So how do we tackle this? Better measurement is key. Looking at use cases and understanding what customers actually want help with, and where automation truly adds value, is essential if chatbots and conversational self-service are to fulfil their promise.

Taking the First Step With AI

With 84% of survey respondents either already using AI or planning to implement it within the next year, the question is no longer if, but how. Steve’s advice is simple and practical: start with a clear business outcome.

That outcome might be cost reduction, or perhaps it is something smaller and more precise. What matters is measuring success against a defined goal, rather than chasing shiny technology without a plan.

Starting small is critical. Steve highlighted the example of a generative AI voicebot that initially routed 100% of calls to agents.

Through gradual refinement, around 30% of interactions are now successfully contained, which is a realistic, effective balance that reflects customer comfort and expectations. It doesn’t have to be 90% – taking into account what customers want is key to hitting the correct balance.

People Matter Most

Finally, our research reinforces that successful AI adoption depends as much on people and data as it does on technology.

Organizations must invest in reskilling employees to operate in a human–AI collaboration model, ensuring uncertainty is replaced with confidence and capability.

It is also essential not to underestimate the effort required to train large language models using internal data.

Knowledge management, training and ongoing optimization are vital to success – and when done badly, they can quickly inflate project timelines and budgets.

Clarity at the outset is key. Being explicit about outcomes, investment and responsibilities is one of the most impactful steps organizations can take today.

The pace of AI innovation in CX shows no signs of slowing, and the year ahead will be defined by those who turn ambition into action. We’re excited to see what’s possible when AI is implemented with purpose.

To find out what else was uncovered in the report, download it for free now: What Contact Centres Are Doing Right Now

Author: Xander Freeman
Reviewed by: Hannah Swankie