When Dell Technologies’ CTO John Roese expanded into the role of Chief AI Officer last year, one thing was clear: they were rallying behind a clear challenge to move fast or get left behind. They set a two-year deadline to do just that and they are on track.

What came next wasn’t hype or hundreds of organic pilots originated from all over the organization. It was purposeful rigor the likes of which has always guided Dell—a multipronged strategy in four clearly defined areas that focused on prioritizing people and processes with technology as the ultimate enabler. Dell delivered $10 billion in new revenue in its fiscal year 2025 with revenue growth of 8% while reducing costs by 4%. That’s a decoupling of the revenue and cost curves rarely seen from a Fortune 50 company.
I was inspired to highlight Dell’s success not because they’re a client (they’re not), but because they offer a compelling playbook for any enterprise embarking on their AI transformation journey.

The Dell way

Here are four nonnegotiables from Dell’s AI startegy that should be on your radar now:

1. Be crystal-clear on why you’re doing AI

There were no feel-good pilots. No AI for the sake of “innovation.” Dell defined early that AI must directly drive profit—through revenue, margins, cost reduction, or risk mitigation. It wasn’t about goodwill or buzz. It was about the P&L, unapologetically.

2. Focus only on what matters
Instead of chasing hundreds of AI projects they had on their list, they identified the parts of the business that truly drive value for them: supply chain, sales, engineering, and customer service. Every AI investment had to serve one of these pillars. According to a recent Stanford Artificial Intelligence Index Report, those four areas are critical levers organizations can use to harness AI to both save and make money. As Roese explained, “We wanted to apply AI against the most impactful processes in the core differentiators of the business to improve our productivity.”

3. Reengineer processes before layering AI

Pre-AI, Dell found the sales team spent a lot of their time navigating workflows and tools. They cleaned up their content, redesigned end-to-end processes, and then overlaid AI on top of it. It’s AI maturity.

4. Build AI systems that scale across the enterprise

Dell avoided the trap of isolated pilots. They chose platforms and frameworks that could serve multiple use cases across departments. AI wasn’t siloed. It was architected for broad, secure, and scalable integration. Whether you’re running a 500-person company or a Fortune 50, the lesson holds: if your AI can’t grow with your business, it’s just a science project.

AI at Scale, the Dell Way

Dell’s AI implementation serves as a core differentiator for them. Here are some high-level nuggets you can take from them to inspire your company’s own AI journey.

• Sales: AI-powered tools cut time spent prepping, giving reps meaningfully more time to be in front of customers.
• Customer Service: Dell-enabled AI to deliver answers with unprecedented accuracy through any interface to resolve customer issues rapidly.
• Supply Chain: AI made Dell’s world-class supply chain more agile, predictive and dynamic in a complex world.
• Engineering: Dell used AI to introduce additional scale to their engineering capability, increasing the capacity and efficiency of their existing team. 

The New AI Blueprint for Enterprises

Dell’s transformation follows a method that any large organization can replicate:

1. Clarify ROI—not goodwill, but bottom-line impact.
2. Identify value pillars—where AI promises to move the needle most.
3. Rebuild, then scale—Redesign broken processes before applying AI. Don’t let automation mask dysfunction. Then incorporate AI only onto those workflows that are optimized to amplify impact fast.
4. Mandate integration & governance—no rogue AI islands allowed. Enterprises are complex and AI use can show up in a variety of places—from SaaS services to procurement and consulting. This is where comprehensive governance comes into play. Make sure you have an active AI use case review board who oversees governance, structure, approval, and prioritization anywhere AI will manifest in your business. No AI projects should proceed without moving through this holistic lens first.

The result? You unleash AI to become an impressive growth engine, enabling the decoupling of revenue from costs curves. Even as a provider of industry-leading AI infrastructure, Dell had to prioritize its people and processes first to drive meaningful transformation, proving that innovation begins with strong process and people foundations.

Why This Matters Now

We’re at an inflection point. Generative AI is not just another productivity tool. It’s a catalyst to rewire entire operating systems. While the headlines fixate on job anxiety or AGI, the real story is about industrial-scale reinvention. Dell quietly became a pioneer again: a 40-year-old company evolving into a living, breathing “AI-first” enterprise.

If you want generational growth, don’t chase every AI trend. Focus on the workflows that actually move your business forward. That’s how you drive ROI, bankroll transformation, and widen the gap between you and the pack.

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When people think about artificial intelligence, they often picture sleek start-ups or futuristic labs. But what happens when AI meets a company that has been innovating for over 100 years?

Unilever is one of the world’s largest consumer goods companies, home to brands like Dove, Hellmann’s and Vaseline, with products used by 3.4 billion people every day. And behind those everyday items is a deep and evolving commitment to science.

From soap and margarine in the early 20th century to today’s breakthroughs in sustainable packaging and personalized skincare, Research and Development (R&D) has always been our engine of progress. But now, that engine is being transformed by AI.

AI is not just a new tool in our labs, it is a new way of thinking. And for a company with a century’s worth of scientific data, that is a game-changer.

AI is reshaping every industry, but the companies that will be the most successful are the ones that know how to adapt, learn, and build on what they already know. While many legacy companies are exploring how to modernize through AI, the real opportunity lies in how they harness their institutional memory: the decades of research, product development, and consumer insights that can often sit untapped. This requires deep domain expertise, robust data stewardship, and a culture that values learning as much as legacy. When those elements align, AI can become a catalyst for transformation, by revealing the full potential of what has come before.

Unilever was born in the Victorian era, shaped by the industrial and scientific revolutions. Over the decades, we have evolved by responding to cultural shifts; from the transformation of domestic life in the mid-20^th century to today’s shifting expectations around skin health, beauty, and wellbeing to the growing urgency of sustainability. When new materials like Formica and stainless steel became common in mid-century kitchens, our scientists developed products tailored to these surfaces. This was not just chemistry, it was a scientific response to a changing way of life.

That same mindset—science in service of real life—still drives us today. But the questions we’re asking have become more complex: How do we support the skin’s natural microbiome? How do we clean homes without disrupting the ecosystems that live on our surfaces? How do we design products that are both effective and sustainable? These are not simple problems, and they require new ways of doing science. That’s where AI comes in.

With machine learning, we can uncover patterns that would take human researchers hundreds of years to detect. We are using AI to understand how microbes interact with our products, how skin responds to environmental stressors, and how we can personalize formulations for different needs and regions.

But here is what makes our approach unique—we are not starting from scratch. Like many legacy companies our R&D archives stretch back over 100 years. We have records of every formulation, every trial, and every consumer insight. This historical depth gives our AI models something incredibly rare: context. While many companies are just beginning to build their data sets, established companies like ours are standing on a foundation that has been carefully constructed for generations.

Our scientists can unlock proprietary knowledge that was once siloed, scattered across teams, or locked in an archive. A century of skincare expertise is now structured, searchable, and ready to be applied. We are using AI to connect the dots across decades of research, accelerating discovery in new materials while simultaneously optimising formulations for specific needs, like different skin types. We’re moving from research and discovery to formulation design and refinement in a single, integrated process, helping us respond faster and more precisely to people’s needs around the world.

This is not about replacing scientists with algorithms. It is about creating the conditions where human talent can thrive. Agentic AI systems give our teams the ability to ask better questions, explore more possibilities, and unlock insights from our data. By amplifying human creativity and empathy not automating it, we’re enabling our scientists to focus on what they do best: imagining, experimenting, and designing products that meet real human needs.

So why should this matter to anyone outside Unilever?

Because it shows what is possible when legacy meets learning. In an era where AI is reshaping every industry, the companies that thrive will not just be the newest or the loudest, they will be the ones that know how to adapt, how to learn, and how to build on what they already know.

AI rewards data maturity. It rewards curiosity. And it rewards companies that see technology not as a threat to tradition, but as a way to reimagine it.

We do not have all the answers. But we have learned that staying curious, being a “learn-it-all” not a “know-it-all,” is what keeps a company relevant for a century. AI is helping us stay curious at scale.

We believe the next 100 years of innovation will be driven by companies that embrace the partnership between human talent and agentic AI: hybrid systems that augment creativity, empathy, and scientific intuition. This is not just a story about technology. It is a story about legacy, learning, and the enduring power of science to shape the everyday—only now with a little help from artificial intelligence.

Alberto Prado is global head digital & partnerships at Unilever.

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