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InterviewCX AI2 Nov 2026 · 4 min read

Why CX Needs to Go Back to Basics in the Age of AI

As customers deploy their own AI agents, EY's Laurence Buchanan shares why CX leaders must return to basics: trust, empathy, and a distinctive value proposition. He explains why cost-led AI can backfire and what that means for customer loyalty and lifetime value.

Author transcript

Sean Nolan: Welcome back to CX Today. My name is Sean Nolan. In the CX market today, it's easy to get lost in the countless product launches and flashy new tools. So with that in mind, is there some value in actually going back to basics? Here to discuss the strategies powering winning CX teams is Laurence Buchanan, Global Leader at EY Studio+. Hi Laurence, thank you so much for joining me on CX Today. I wanted to start by discussing the idea of why customer experience is going back to basics. Can you tell me about what you're seeing in the CX market at the minute, and why simplicity is becoming more valuable? Laurence Buchanan: Yeah, look, thanks Sean, firstly for having me on. It's really, really great to be with you today. I think what we're seeing in the market at the moment is customer expectations are rising like hyperinflation. Most organizations have been through quite a tumultuous period of change: technological change, societal change, geopolitical change. In that environment, it's quite easy for companies to become quite reactive, to jump from pilot to pilot just to try and keep up with a market that's moving far quicker than it's possible to keep up with. Now, my view is that back to basics is actually just saying, let's pause for a moment and let's put the customer at the heart of our business and work backwards. That's simple 101. If we can really understand the customer, their wants and needs, we stand a chance of designing and building differentiated products and experiences, and aligning the organization behind that. And to me, that's the philosophy of back to basics, really. Sean Nolan: Yeah, absolutely. Thank you. And I think right now there's this balancing act of, as you say, keeping the customer at the heart of your CX team. There's also this ever-present need for digital transformation and keeping up with your competitors, and there's a lot going on in that space as well on the innovation side. So what do you think is separating winners from the rest of the pack when it comes to digital transformation and that philosophy of going back to basics as well? Laurence Buchanan: Yeah, look, I mean, the customer's expectation is rising like hyperinflation. It's set by their last best experience across all providers that they deal with. So by definition, it's moving faster than anyone can keep up with. The winners, I think, are not necessarily the ones that are just implementing technology the fastest or using the most technology. They're the ones that are really, number one, building deep empathy with their customers. Really taking the time to understand customer wants and needs. We did some research recently called the Future Consumer Study. We're trying to look at what's on the minds of consumers today, and we found that if organizations are overwhelmed with the speed at which technology is moving, actually so are customers. 65% feel digitally overwhelmed right now. 79% want technology, but only if it's making their lives simpler and more convenient. So I think the first thing that the digital transformation leaders are doing is that they're really taking the time to build that empathy with the customer. Secondly, you could argue that AI is, to some extent, democratizing it. It's putting really strong power and reach into the hands of every marketeer around the world. So the pressure, to me, is to create differentiation, so that the leaders are absolutely embracing technology and innovation, but they're doing so to try and build differentiated, distinctive products, services and experiences. And then the third and final thing that they're doing, this is nothing more than relentless execution. Behind every brilliant customer experience is a supply chain that needs aligning, is people, skills and culture that need aligning, is a whole ecosystem of different providers that needs aligning. So unfortunately, there's no getting round this. This is a game of relentless execution. Sean Nolan: Yeah, no, absolutely. I think the point you made there about empathy is really important. As you say, customers really value that simplicity and that convenience. They don't really care what kind of technology companies have running in the background and how they're using AI, et cetera. It's just about their personal experience and that interaction. So I think that's really spot on. And as you say as well, it's about the wider ecosystem. It's not just the contact center, for example, that manages the whole CX customer journey. It's actually a wider thing, with supply chain, et cetera. So all these points are really separating those winners, as you say. So thank you so much. I want to pick up what you said earlier about the hyperinflation of expectations in the consumer and buyer. How does what we've talked about so far tie into that, and how are we trying to meet the expectations of this modern customer, who is more informed than ever thanks to AI on the customer side? How are businesses able, or looking, to match those expectations of customers who are really informed? Laurence Buchanan: Yeah, look, I think what becomes really critical to compete in that environment is trust. And what we're seeing now is that consumers' trust with organizations is at an all-time low. In our Future Consumer research, we found something like two-thirds of customers said their skepticism has increased. Their trust in corporate brands is lower than it's ever been. They trust independent experts more than they trust corporate brands. That's a really challenging position to begin with, because trust is something that is built over many, many years through reputation and through delivery, but it can be lost in an instant. The moment your marketing message promises something that the organization can't deliver. The moment you, for example, misuse customer data. The moment that a customer support representative is having a bad day and doesn't fix the problem brilliantly, trust can suddenly be eroded very, very quickly. But to me, it is the critical currency to try and compete, to have even the right to engage with consumers and compete, particularly in a world where AI is becoming an important part of the customer's journey. Sean Nolan: Yeah, absolutely. Thank you. And I think as part of that trust as well, there's this balancing act at the minute where businesses are looking to adopt more technology, and I think there's a whole variety of reasons for that. But can you tell us about where you see human team members playing a role in the future of customer experience as well? Because we have all this innovation right now, but at the end of the day, it's down to how you optimize that technology, and I think that optimization comes from the teams and the culture and the humans behind all of it. So could you speak a little bit about that? Laurence Buchanan: Yeah, I think that's a really great point. If you step back and look at the last few years, we've seen, with AI, one of the biggest technology revolutions that any of us have ever lived through. But that period of technology revolution coincided almost to the day with a period of economic and geopolitical tension. Most economies are struggling to really drive growth right now. And so you could argue that at exactly the right moment, where CEOs were genuinely looking to drive productivity and cost savings, AI comes along as this silver bullet that can strip out cost. And so the easy temptation there was to say, well, let's point AI at marketing, because AI can eliminate 30 to 40% of cost from our content supply chain. Let's point AI at customer support, because AI again can drive 100% level one customer support. The challenge, I think, is what about the secondary consequences of that? Any research you will ever read says that your most loyal and profitable customers typically are ones that have been through service recovery. In other words, they've had an issue, and the organization, and typically people within the organization, have fixed that problem so well that it's driven a kind of emotional loyalty, and as a result their loyalty, their lifetime value, has gone up. If you don't have those friction points with AI, do you miss out on that secondary effect to drive loyal customers? Similarly, if I take marketing, for example, just because you can use machines to produce an abundance of personalized machine-generated content, is that actually the right thing to do? The content typically is adequate but also mediocre. It's not necessarily driving competitive differentiation, because it's lacking sometimes that spark of human creativity. And that might not show up straight away, but maybe over time, what we're driving actually is something even worse. We're driving apathy. We're no longer relevant in the lives of our customers, because we're producing bland, mediocre content. So for me, the secondary impacts of automation are really important to consider when we think about the end-to-end customer experience. Sean Nolan: Yeah, definitely. I think a theme from what you said there is that to build that strong customer trust, you need a bit of human in the mix, whether it's in marketing or in your customer experience team, for example. You need a bit of that human-to-human engagement and interaction that AI can't reproduce, and that, as you say, creates that emotional relationship there and therefore builds customer loyalty from there. So that human relationship still plays such an important role in that CX outreach, and that's definitely something enterprise leaders should keep in mind moving forward. I think, taking a step back and sharing your advice for CX leaders, in your experience, what's one big mistake that you see a lot of CX leaders making too often at the minute? Laurence Buchanan: I think, probably building from the last point, going into AI thinking it's just about cost savings and productivity is a real error. I think you need to be greedy and go in and say, we want cost savings, of course, but we also want increased customer loyalty, lifetime value, we want to drive a better experience. What we typically see, in the last few years of piloting AI relentlessly everywhere, is there's been lots of what I call bolt-on AI experiments, which is simply bolting on an AI application to the way things used to work yesterday. Now, in many cases, that is not even driving the first goal of productivity, because it's actually making things more complex. It's adding another channel or another process. It's making it more expensive and more complex. A better approach, for me, is saying, if these are the business goals that we want to achieve: reduce costs, increase revenue, better experience. How do we reimagine the end-to-end operating model with AI at the heart to try and make that happen? And that is never just a technology implementation. It's reimagining the way we work, how work gets done in the system. The biggest challenge for me from AI is that it's an operating model change, not a technology change. Sean Nolan: Yeah, absolutely. I think one thing we've seen a lot in research is that when you bolt on AI, as you say, in a kind of unnecessary way, or you're not truly integrating it into the workflow or rebuilding the workflow appropriately, actually what you do is you create more work for your employees, because now there's another step in the process, and they're having to manage the AI rather than the AI coming in and solving all these issues in their workflow. So I think it can create the opposite problem, as you say, and hamper productivity if not done correctly. So I think that's absolutely spot on. That's a really key observation there. And finally, I wanted to ask a forward-looking question. As we head into the final few months of 2026, do you have any predictions for what's in store for the CX landscape in 2027 and beyond? Laurence Buchanan: Yeah, look, it's interesting. Like everyone, I've been, for the last three, four, five years, just reading about AI in customer experience, attending conferences, listening to podcasts, really trying to educate myself in this space. What I observe is 99% of content is written about AI for the benefit of the company. 99% of content is: AI can help improve your marketing, AI can help improve customer support, AI can drive sales. It's all focused on the company's benefit. We are missing one really, really fundamental thing, which is that customers will also use these tools themselves. And to me, that is the biggest shift in customer interactions since the birth of the internet. What I see happening is customers actually starting to deploy their own AI agents to interact with organizations. And so maybe we see this rise of a brand-new intermediary, which is the customer's AI agent. And that might be a huge threat to some organizations, because it might mean that they completely lose control of the customer interaction layer. We're already seeing the rise of some agents, for example, that are negotiating telco or utility tariffs. They are initiating conversations with a provider's chatbot. And this is a pure machine-to-machine interaction. A customer's personal AI is trying to negotiate a better deal from the organization's chatbot. So this is pure machine-to-machine in the customer interaction layer. I think that's a real threat, and I think the way through that, maybe, is to go back to our opening theme. Organizations have to build a unique and differentiated customer value proposition. There's just no other way around that. They have to really understand not only the wants and needs of the customer, but also just basics like customer lifetime value and the economics of customer loyalty. I think, armed with those insights, we stand a chance. We can apply creativity, design thinking, build new products and services, execute and implement behind the scenes. But to me, that's the emerging threat that I'm seeing in the market right now. Sean Nolan: Yeah, definitely. I think, as you say, the next step will be agents talking with the agents deployed by the business, and it'll be this machine-to-machine relationship. And I think that, as you say, could be a threat to so many industries right now. Particularly, even for example, something like marketing, where we don't need to connect with the human anymore, we need to develop our marketing around attracting the AI agent, the personal AI agent of these consumers. So it really changes the landscape in a lot of different ways. And as you say, it's definitely something that I'm sure you, and I'm sure us as well, will be keeping a really close eye on moving forward. So yeah, absolutely, really spot-on observation, and thank you so much for your time today, Laurence. It's been great speaking with you. Laurence Buchanan: My pleasure. Thanks, Sean. Sean Nolan: Thank you for watching. For more insight into what makes a successful CX team, create your account on cxtoday.com and don't miss another interview like this.

Every week brings another product launch, another pilot, and another promise that AI will fix the customer experience. For many CX teams, keeping up has become the strategy.

But the pace of change is hitting customers as well as companies. If both sides feel overwhelmed, the organizations that win may be the ones that stop chasing tools and start with the customer.

Laurence Buchanan, Global Leader at EY Studio+, tells CX Today why the answer to rising customer expectations may be to slow down and take CX back to basics. He also warns that customers are about to bring their own AI agents into the conversation.

What Does Going Back to Basics Mean for CX?

Buchanan describes customer expectations as rising "like hyperinflation," and says that has pushed many companies into a reactive cycle of jumping from pilot to pilot. His answer is to pause and work backward from the customer:

"Back to basics is actually just saying let's pause for a moment and let's put the customer at the heart of our business and work backwards."

He sees it as a philosophy, not a project. If a business understands its customers' wants and needs, he argues, it stands a better chance of building differentiated products and experiences, and of aligning the organization behind them.

What Separates CX Winners From the Rest?

According to Buchanan, the leaders are not necessarily the ones implementing technology fastest. He points to three habits: building deep empathy with customers, using technology to create differentiation, and what he calls relentless execution.

He also cites EY's Future Consumer Study, which found that 65% of consumers feel digitally overwhelmed and 79% want technology only if it makes their lives simpler and more convenient.

On execution, he says there is no shortcut:

"Behind every brilliant customer experience is a supply chain that needs aligning, is people, skills and culture that needs aligning, is a whole ecosystem of different providers that needs aligning."

Why Has Trust Become the Currency of CX?

Buchanan says consumer trust in organizations is at an all-time low. In the same study, he notes that about two-thirds of customers said their skepticism had increased and that they now trust independent experts more than corporate brands.

That makes trust both fragile and essential. A broken promise, a misuse of data, or a poor support call can undo years of reputation, and in a world where AI plays a bigger part in the customer journey. Buchanan describes trust like this:

"It is the critical currency to try and compete, to have even the right to engage with consumers."

Where Does Cost-Focused AI Go Wrong?

Buchanan believes many leaders were tempted to point AI at cost, from cutting content production costs to automating level one customer support. The risk lies in the secondary effects. He notes that the most loyal and profitable customers are often those whose problems were fixed brilliantly by a person, which raises a question about what is lost if those friction points disappear.

The same applies to marketing, where he warns that an abundance of machine-generated content can be adequate but mediocre. Over time, he suggests, the result could be worse than a missed opportunity:

"What we're driving actually is something even worse. We're driving apathy."

His advice is to be "greedy," and to want loyalty and lifetime value as well as savings. He also criticizes "bolt-on AI experiments" that add complexity to old ways of working and argues that AI is an operating-model change, not a technology change. We'll leave the rest of that discussion for the video.

What Happens When Customers Bring Their Own AI Agents?

Buchanan's final prediction is the one he thinks most companies are missing. He says 99% of AI content in CX focuses on the company's benefit, yet customers will use these tools too. He expects customers to deploy personal AI agents that interact with organizations on their behalf, creating what he calls a new intermediary.

Early examples include agents negotiating telecom or utility tariffs with a provider's chatbot, a purely machine-to-machine exchange. Buchanan described what this could mean for brands:

"That might be a huge threat to some organizations because it might mean that they completely lose control of the customer interaction layer."

His answer is to return to the opening theme. Organizations need a unique, differentiated customer value proposition, grounded in a real understanding of customer lifetime value and the economics of loyalty.

The Bigger Picture

Buchanan's argument is that CX leaders do not need to move faster than the market, they need to be clearer about what customers value. That means treating trust as an asset, keeping people where emotion and judgment matter, and redesigning how work gets done, not bolting AI onto old processes.

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