As artificial intelligence reshapes the digital economy, customer experience is becoming one of the most visible frontiers of transformation. From conversational AI to autonomous virtual agents capable of executing complex tasks, platforms are evolving rapidly. With more than 8,000 organizations using its solutions worldwide, Genesys sits at the center of this shift, helping companies orchestrate interactions between customers, employees, data and AI.

In this conversation, Guillaume Lardeux, Head of Transformation and Office of the CEO at Genesys, shares his perspective on how AI is transforming customer relationships, why many companies are still struggling to adopt it at scale, and how technologies such as agentic AI and Large Action Models could redefine the next generation of enterprise platforms.

Q. How would you describe Genesys today, and your role in shaping the future of customer experience?

A. Genesys is the experience orchestration platform that empowers enterprises to create the best customer and employee experiences. Our focus is helping organizations move beyond isolated interactions to deliver connected, end-to-end experiences that drive both efficiency and loyalty.

In my role, I focus on driving transformation across the company, with AI at the center of that work, whether that’s modernizing our systems and processes, shaping our IT strategy, or embedding AI more deeply into how we operate and deliver value to customers. A big part of what I do is making sure everything connects across strategy, technology, data and operations so we can move quickly and stay aligned as the market evolves.

Q. AI is now at the center of how companies interact with their customers. Beyond the hype, what is really changing today in customer experience?

A. What’s really changing is a shift from answering questions to delivering outcomes. Customers don’t just want faster responses. They want their problems solved, end to end, with efficiency and empathy.

AI has evolved from simple automation to systems that can understand intent, adapt in real time, and take action across workflows. This is what we describe as moving from conversational AI to agentic AI, where systems can reason, plan, and execute responsibly.

At the same time, expectations have changed. Customers don’t compare you to your direct competitors anymore. They compare you to the best experience they’ve ever had. So, the bar is much higher. It’s not just about speed, it’s about being relevant, personalized and emotionally intelligent.

Q. In that context, where does Genesys fit in this transformation, and what is your core approach to customer experience?

A. For us, it really starts with the platform. Genesys Cloud is our AI-powered experience orchestration platform that brings together people, data, systems and AI into one unified environment.

What that means in practice is that we’re not just helping companies manage interactions, we’re helping them orchestrate entire end-to-end experiences. Across channels, across touchpoints, and across the full customer and employee journey.

The platform embeds different types of AI—agentic, generative, conversational and predictive—so you can automate tasks, augment employees, personalize every interaction and continuously optimize outcomes. And because it’s all connected, it learns over time. Every interaction feeds the system, making experiences smarter, more contextual and more effective.

So, our approach is really about moving away from fragmented tools toward a single platform that can coordinate everything in real time. Ultimately, that helps companies shift from reactive service to proactive, personalized engagement at scale.

Q. The Customer Experience market is highly competitive. Where do you see your clearest differentiation today?

A. Our differentiation is that we’re not a collection of point solutions. We’re a unified platform built with AI at its core for experience orchestration.

A lot of the market is still very fragmented. You have a bot here, a copilot there, some analytics somewhere else. And then the customer has to stitch everything together. We’ve taken a different path. Genesys Cloud is a single platform where all these capabilities—automation, augmentation, personalization, optimization—work together in real time.

Another key differentiator is our data. We operate at a massive scale of real-time interactions, which gives us a depth of context and insight that allows AI to make better informed decisions, personalize experiences more effectively, and continuously and responsibly improve outcomes.

Another critical piece is openness. We integrate deeply with platforms like Salesforce and ServiceNow, and we’re investing in standards like MCP and A2A so AI agents can collaborate across systems.

So, for us, differentiation is really about orchestration and bringing together AI, data, and the entire ecosystem in a way that works seamlessly at scale.

Q. What does a good customer experience actually mean today, and how is that definition evolving with AI?

A. A good customer experience today is about being efficient, effective and emotionally intelligent. In other words: solve my problem, don’t waste my time, and treat me right.

What’s evolving with AI is the ability to deliver all three simultaneously, at scale. In the past, companies often had to choose between efficiency and personalization. Now, AI makes it possible to achieve both.

The definition of great customer experience is shifting from speed alone to how quickly and effectively a customer feels understood.

Q. AI and automation are everywhere, yet many companies still struggle to deliver real results. Where do you see the biggest gap between ambition and execution?

A. The biggest gap is that many companies are still thinking about AI in terms of tasks not outcomes.

They’ve deployed automation in isolated use cases, for example chatbots, copilots, routing, but those systems often lack context and break down when complexity increases. So, you end up with isolated improvements, but not real transformation.

There are also structural challenges, like legacy systems, siloed data and disconnected tools, that make it hard to scale. And sometimes, companies start with the technology instead of the outcome. They ask “where can we use AI?” instead of “what problem are we trying to solve?”

The organizations that succeed are the ones that take a step back and redesign the experience end to end, with AI as a core part of it—not just an add-on.

Q. Trust is becoming a critical issue as AI systems move from answering questions to taking actions. How do you ensure reliability, control, and transparency in these systems?

A. Trust comes from combining autonomy with accountability. As AI systems begin to take action, they must operate within clear guardrails, including governance, human oversight, and defined objectives. That’s why orchestration is so important. It ensures that every action is aligned with business goals and customer outcomes, and that there is transparency into how decisions are made.

At the same time, empathy plays a critical role. Systems that understand context and intent build confidence because they behave in ways that feel aligned with human expectations.

Q. From what you observe across your clients, what does it concretely take to move from experimentation with AI to real, scalable impact?

A. It requires a shift from pilots to platforms. The companies that succeed treat AI as an operating model, not a feature. They orchestrate experiences end to end, connect data and workflows, and align around outcomes.

They also focus on combining human and digital labor effectively. That is, using AI to handle complexity and scale, while empowering people to deliver empathy where it matters most.

Q. Looking ahead, how do you personally see customer experience evolving over the next five years?

A. We’re moving toward a world where experiences are much more autonomous, proactive and connected.

AI won’t just respond. It will anticipate needs, coordinate across systems, and take action to deliver outcomes. Experiences will feel less like a series of interactions and more like a seamless, ongoing relationship. We often describe that as moving toward universal agentic orchestration.

At that stage, AI is no longer following predefined workflows. It’s operating with goals, and is planning, deciding and executing dynamically to achieve outcomes. Multiple AI agents can collaborate across systems and organizations, sharing context and coordinating actions in real time, while humans stay focused on oversight and high-value decisions.

The companies that get it right will be those that combine efficiency, empathy, and intelligence at scale. They’ll use AI not just to reduce cost but to build loyalty and long-term growth. Those that fall behind will remain stuck in fragmented, transactional models where they are optimizing parts of the experience rather than the whole.