Customer Experience and AI: a love story in the making

Ah, customer experience (CX)—the art of making people feel good about your brand at every turn, from the website visit to the product purchase and beyond. Done right, CX transforms customers into loyal fans. But here’s the kicker: delivering an amazing CX isn’t easy.

Think about it. To really nail CX, you must read minds (or at least come close), anticipate customer needs, design flawless experiences, and keep it all fresh and exciting. This can be exhausting but fear not; AI is here to help.

In this blog, we examine the relationship between customer experience (CX) and artificial intelligence (AI), highlighting both the opportunities and potential challenges of using AI to enhance customer interactions. We also look at some of the common reasons behind the failure of AI initiatives, and how capitalising on AI, especially generative AI (GenAI), has the potential to revolutionise the way brands engage with their customers.

By the end, we hope you will understand a little better why a harmonious integration of AI and CX is crucial for delivering exceptional, personalised experiences that turn customers into devoted advocates.

AI: The BFF* Customer Experience never knew it needed

Imagine artificial intelligence as a friend who shows up with a superpower just when you need it. Generative AI, in particular, is like that friend, revolutionising customer experience by helping brands collect, analyse, and act on customer data more effectively than ever before.

In doing so, GenAI offers capabilities that redefine how businesses engage with customers—enabling personalised interactions, rapid query resolution, and remarkably accurate product recommendations (yes, it knows you even better than your bestie).

Now picture a chatbot that not only provides accurate answers to your questions but also recalls your preferences, like your favourite coffee order. Or an email that knows you’re a night owl and arrives at 10pm with a perfectly timed, irresistible offer. These are just a few of the possibilities AI unlocks. But wait—there’s a plot twist.

*Best friends forever.

AI needs CX too

Yes, you read that correctly. While AI might seem all-powerful, without a clear connection to customer experience (CX), it’s like a superhero without a mission. Simply put, AI is a tool, and tools are only as effective as the purpose and strategy behind their use. Without CX, AI becomes directionless—like a chef preparing a dish without tasting it or a comedian cracking jokes without understanding the audience. You get the idea.

The true power of AI lies in how it’s intentionally aligned with customer needs and experiences. For this to happen, CX has to take the lead and bring the human touch—ethics, empathy, and a focus on solving real-world problems—into the equation. Customer experience ensures that AI doesn’t just wow people with how smart it is but also delivers value in a way that resonates.

Aligning AI with CX is also about responsibility. When guided by CX principles, AI becomes not only smarter but more trustworthy. Let’s explore how this works.

How CX keeps AI on track

It’s important to be aware of the challenges associated with using AI and how customer experience (CX) plays a key role in addressing them. Left unchecked, AI can run into some sticky territory:

• Biases: AI learns from us and, let’s be honest, humans have some messy biases. For example, a hiring AI might unintentionally favour male candidates for tech roles if the training data reflects historical gender imbalances. CX teams can keep AI on the straight and narrow, ensuring fairness and inclusivity by refining data inputs, auditing AI decisions, and ensuring transparency in the hiring process.
• Privacy: nobody likes a nosy algorithm. Think of personalised marketing campaigns that cross the line, like when a retailer predicts a customer’s pregnancy before their family knows, simply by analysing their purchase history. CX ensures these systems respect personal boundaries and implement opt-ins, clear disclosures, and ethical data usage policies that prioritise customer trust. With CX as a guide, businesses can create experiences that feel personalised without invading privacy.
• Relevance: chasing shiny new tech may be tempting, but does it solve a real problem? CX makes sure AI stays grounded in what customers actually need. Consider a bank rolling out an AI chatbot that only confuses customers with irrelevant responses instead of helping them resolve their issues. By grounding development in CX principles, companies can ensure chatbots provide clear answers, learn from user feedback, and escalate complex issues to human agents when needed.

Involving a CX team in the development of AI-based solutions and applying CX principles can significantly help avoid these pitfalls and mitigate real-world risks like those mentioned above. However, even with the best intentions, AI projects may still face other challenges and no success is guaranteed.

Why do AI projects fail? Ask the specialists

AI is like the cool kid in tech—smart, flashy, and full of potential. But even the cool kids stumble sometimes. Surprisingly, a significant number of AI and machine learning (AI/ML) projects don’t make it to the finish line.

To uncover why this happens, the RAND Corporation conducted a study titled, ‘The root causes of failure for artificial intelligence projects and how they can succeed.’ Researchers went straight to the source: they surveyed 65 seasoned data scientists and engineers with five or more years of experience in building AI/ML models. They identified five common pitfalls. Of these, three particularly stand out to us:

1. Misunderstanding the problem AI is supposed to solve.
2. Getting distracted by flashy tech instead of focusing on user needs.
3. Tackling problems that are too complex for AI to handle.

These findings are enlightening—and they likely strike a familiar chord. After all, these are classic CX missteps as well. The solution is to pair customer experience and AI like bacon and eggs—two things that are good on their own but amazing together.

The power of CX-driven AI

AI solutions that fail to prioritise user needs risk irrelevance, inefficiency, and even a loss of trust. By contrast, CX-led innovation—placing user experience at the heart of its design and implementation—ensures that AI does more than enhance operational efficiency. It addresses real-world needs, builds trust, and creates value in ways that matter.

In the end, CX isn’t just a nice-to-have—it’s the guiding force that turns AI into a superhero with a mission. Here are a few recommendations to consider:

1. Clarify the problem before jumping into AI: ensure that AI is being used to solve a specific, well-defined problem. The project’s scope should be grounded in customer needs and pain points. For example, if AI is meant to enhance customer service, make sure it’s addressing clear issues, such as long wait times or inconsistent responses.
2. Focus on the end-user: technology is only as useful as its relevance to the user. Incorporate user feedback early in the development process to ensure the solution solves actual problems. Engage with customers through surveys, focus groups, and pilot testing to refine your approach.
3. Define clear objectives and expectations: to avoid the pitfall of chasing after overly complex AI solutions with unclear returns on investment (ROI), set achievable goals that align with both the customer journey and business objectives. that match the capabilities of the technology and your team, ensuring that all stakeholders understand the project’s purpose, how it will be used, and what success looks like. Starting with manageable goals allows for learning, adaptation, and iteration, paving the way for long-term success.
4. Ensure cross-functional collaboration: involve a CX team from the outset to guide the AI’s design and implementation. Close collaboration between AI specialists, CX professionals, and business leaders will ensure the project is both technically sound and customer centric.
5. Monitor and iterate: once the AI system is deployed, continuous testing and iteration are key. Run pilot programmes, use A/B testing to refine AI-driven processes, and ensure that AI is always in sync with evolving customer needs and behaviours. Collect feedback from real users and make improvements in response to any challenges or shortcomings.

By pairing AI with CX from the outset and keeping these principles in mind, companies can significantly increase their chances of success. While embarking on this journey may feel overwhelming, adopting a strategic approach turns it into an exciting opportunity to transform customer experiences. The best part? You don’t have to navigate this path on your own.

Innovating with purpose – PwC GenAI Business Center

Located at the Experience Center, PwC Luxembourg’s GenAI Business Center is the ideal place for applying a customer-first mindset to AI solution development. Using design-thinking methodologies, our CX team collaborate with our technology and business specialists to help organisations anticipate and address real challenges, foster emotional connections and build trust.

The GenAI Business Center offers a collaborative environment where organisations involve their employees and customers in the co-creation of AI-enabled solutions. Their engagement ensures the solutions are designed to improve existing processes and solve specific pain points.

Co-creation also fosters a sense of ownership among stakeholders, driving adoption rates and minimising resistance to change. Ultimately, the GenAI Business Center transforms AI projects from a purely technological initiative into a collaborative innovation that empowers users and delivers value. By placing people at the centre of the process, organisations can ensure AI solutions are not only effective but also trusted and embraced by those they serve.

The emerging trend around AI agents (software that perform tasks on behalf of users) will force organisations to evolve toward a more collaborative model where humans and AI work in tandem to drive efficiency and unlock new opportunities for skill development and growth.

The takeaway

CX and AI aren’t just collaborators—they’re soulmates. CX helps AI stay ethical, relevant, and impactful, while AI supercharges CX to new heights. Together, they create experiences that delight, inspire and build loyalty.

The love story between CX and AI is sustained by empathy and commitment to address real-world needs. By embedding user-centricity into every stage this love story isn’t only compelling but genuinely transformative.

What we think