March 11, 2026

Inside LabX: How DXC Technology builds AI solutions that actually work for enterprises 

DXC Technology recently launched LabX at a moment when the question facing every large enterprise is no longer whether to adopt AI, but how to do it with both speed and discipline to drive tangible impact. As DXC's internal startup incubator, LabX brings together customers and skilled professionals from across the organization to turn business challenges into working AI-native solutions – fast. Every idea is born of a real customer challenge and must earn its way forward. Nothing scales without proven, measurable results.

To understand how LabX works, the challenges it aims to tackle for enterprises around the world, and where it is headed, four of DXC's senior business leaders share their insights in the following Q&A: Holly Grant, Senior Vice President of Strategy and Innovation; Daniel Padilla, Chief Technology Officer of LabX, AI Enablement & Enterprise Architecture of DXC; Russell Jukes, Chief Digital Information Officer leading the technology vision; Anthony Pappas, Chief Marketing Officer overseeing user experience.

How does LabX fit into DXC’s broader innovation strategy?

Holly Grant: LabX is a direct extension of DXC's Fast Track initiative, which aims to accelerate the development and deployment of AI-infused solutions for our customers. It gives us a dedicated space to experiment, move quickly, and work with AI in new and novel ways, without the constraints that typically slow innovation inside a large enterprise.

We think of LabX as a way to operate at the frontier of what's happening in AI, where we use the latest tools and bring startup velocity into an enterprise context. The goal is to create the conditions where we can develop new offerings for our customers, not just refine what already exists. And because we move fast and with discipline, we can graduate ideas within a very short time frame – ideas that inform new business models, new products, solutions and platforms that we’re ready to bring to market.

What truly sets us apart, however, is who we test with first. DXC's willingness to be Customer Zero is central to LabX. As an enterprise navigating the AI era, we face many of the same challenges our customers do, and that gives us a unique advantage. We develop and test ideas against our own real-world complexity – 115,000 colleagues across 70 countries, with significant regulatory and operational considerations – guided by DXC’s AI orchestration blueprint, Xponential, before we bring them to market.

What a traditional startup can't easily replicate is that lived experience of operating inside complexity. If a solution can survive and deliver value in our environment, that's a strong signal it will do the same for our customers. When we approach clients with an offering, we can say we've battle-tested it ourselves and show them exactly what it delivered. That's a very powerful conversation to be in.

Why did DXC create LabX?

Anthony Pappas: We created LabX because we are in a new era, one that is moving very fast and heading in directions that even the most informed people can't fully predict. To flourish in that environment, you must innovate. And innovation means trying, where not every attempt will succeed. You need a mechanism that keeps you in motion regardless, one that lets you test quickly, learn fast, and move on without losing momentum.

That is what LabX is built for. What's striking about this moment is how much of what we've done for 20 years is now being fundamentally rethought. AI has long carried that promise, and now you can actually deliver on it.

LabX also taps into something powerful inside DXC: the depth of talent and ideas across our organization. We recently ran an AI challenge within one of our business units and generated over 1,300 unique ideas in two weeks. At the heart of that response is our Human+ approach, which holds that humans must remain at the center of AI, driving the processes and strategies for how the technology is used.

As AI frees up time by automating the routine and surfacing information faster, the critical question becomes what people can do with that time. This could range from thinking more clearly, collaborating more effectively or adding greater value to their teams or customers. That kind of energy doesn't happen by accident. It happens when you build the right conditions for it, and LabX creates those conditions.

What's the bigger vision for how LabX seeks to enhance the way people work?

Russell Jukes: For decades, large enterprises drove efficiency by standardizing virtually every process, technology and policy. Instead of becoming more efficient, employees began spending more time navigating one system after another. All day, every day, people are moving between systems to hunt for what they need.

What if we flipped that entirely? Instead of employees going to the technology, the technology comes to them. Instead of asking how efficiently someone can operate a standard process, we ask how efficient we can make that person in the way they actually work. That's the shift from the standardized enterprise to the personalized enterprise, and it's a fundamental one.

Part of what makes LabX so valuable is that it gives us the space to test these ideas, to try new technologies, and to challenge some deeply held assumptions about how people consume technology at work. As AI automates routine tasks and surfaces information faster, people can redirect their energy toward strategic thinking and creative problem solving that help drive organizations forward. The goal is rethinking the relationship between people and the tools they use to get things done faster but also in a meaningful way.

How do leaders at LabX think about the future of AI as it becomes more embedded in the way people work?

Russell: We still talk about AI the way we once talked about the Internet — as if it's something separate or something you consciously choose to use. That will change. The question won't be "what AI are you using?" It will simply be "what outcome are you trying to reach?"

That's the shift we’re building toward. The more we can abstract the underlying technology and get people closer to the outcome they're trying to achieve, the faster they can get there.

Since the dawn of IT, we added tools to the way we work – word processors, databases, collaboration platforms – each promising to make us faster and more productive. But that is not the conversation anymore. AI is not another tool to add to existing ways of working. It delivers value when we fundamentally change how we think about what it can do for us and what we can do with what it gives us. 

And because we've built LabX with portability in mind, we can swap out technologies and evolve capabilities as the landscape changes, without disrupting the experience for the people using it. What stays constant is the focus on the outcome. Everything else is just the means of getting there.

How does LabX think about the experience of the individual at work?

Anthony: Our focus is on the individual and the unique personas that exist across an enterprise. We recognize that different functions within an organization work differently, with distinct processes, workflows, and ways of thinking. So rather than building generic tools, we are building solutions tailored around specific personas and the daily tasks, decisions, and content that define how they actually work.

Three innovation areas are shaping our thinking right now. The first is conversational intelligence: finding information today requires jumping in and out of multiple systems, so we are exploring a future where you simply verbalize what you need and AI surfaces it for you, naturally and in real time. The most intuitive interface is conversation, and that is the direction we are headed.

The second is agentic automation. Right now, most knowledge workers spend roughly 80 percent of their time searching, gathering, and organizing information, and only spend 20 percent of their time actually doing something with it. We are working to flip that ratio. If AI handles the heavy lifting, that 80 percent shrinks dramatically, and people can redirect their energy toward higher-value work. That is a fundamental reimagination of how work gets done.

The third is unified collaboration. Today, working with colleagues means navigating multiple disconnected systems. We are developing a unified space where data, collaboration, and agentic AI come together in real time, in one place. That environment does not fully exist yet, but it is what we are building toward.

Taken together, these innovations share a common goal: enhance the way people work and make them exponentially more productive so that the technology becomes an extension of how they think, collaborate and operate versus a tool they simply use.

How does LabX ensure what it builds is secure and can be trusted?

Daniel Padilla: Because we're working with rapidly evolving technologies, security, privacy, and compliance aren't afterthoughts. They're built in from day one. Every product goes through a formal governance review baked into the infrastructure; every project must prove itself with a real customer before it scales, and every product that leaves LabX comes with a full responsible AI sign-off.

That matters because the challenge we're trying to solve is bigger than the products themselves. Right now, AI comes with a lot of noise and a lot of hype. For customers trying to understand what's real, what's viable, and how to implement it well, the landscape is genuinely difficult to navigate. What LabX offers is a different way forward, a disciplined model that delivers AI value quickly, without sacrificing rigor.

Practically speaking, our team stays current on the latest AI tools and how to apply them. But knowing the technology is only part of it. What drives everything we build is a deeper understanding of how the end user will gain lasting value from using it.

What innovations are LabX developing so far?

Daniel: We have multiple products currently under development that reduce the time employees spend searching for information or pulling together repetitive reports, as well as a platform that lets people experiment with AI safely and learn by doing. Across a range of functions, from sales to HR and finance, we're identifying ways to improve processes and workflows, proving value, then scaling what works. Nothing moves forward without demonstrated, measurable results first.

Beyond the customer impact, how is LabX shaping the way DXC's own people work?

Holly: Technical experts from across DXC complete 6-12 week rotations through LabX, learning cutting-edge AI while building real products. When they return to their teams, they bring more than new skills. They bring a different way of thinking. They ask different questions of their colleagues, model what's possible in the work that they continue to do for our customers, and become champions for innovation in their home organizations. That is a powerful feedback loop, and it is entirely by design.

We also recognize that this is new terrain for everyone, including us. The best way to learn it is to be a practitioner: using the tools, pushing their boundaries, and doing that week after week as the landscape shifts. We believe that hands-on experience creates a network effect that ripples across DXC, whether someone is in a corporate function or delivering for a customer. The implications for how we reimagine the future of work are significant.

This is also a direct expression of DXC's Human+ approach to AI, which is fundamentally about amplifying human potential. At LabX, that means bringing together human collaboration, generative AI, and increasingly agentic AI. When those dynamics intersect, the results are exponential. We become more productive, find new ways to work together, and do more than we could before.

Ultimately, that is both the strategy and the business case. An organization where people are genuinely better at what they do, individually and collectively, is an organization that delivers more for its customers. Everything we build at LabX works toward that goal.