Paolo Pellegrini is a Partner at Metyis, supporting large organizations in using data and AI to improve decisions and build innovative business models. With cross-sector experience, he focuses on embedding intelligence into operations and strategy. In 2019, he led the launch of an AI Product Factory, developing LLMs that combined generative AI and optimization to enhance Marketing performance. Before Metyis, he held leadership roles in top Italian consultancies and began his career as a researcher at Politecnico di Milano, exploring early trends like Big Data and Cloud Computing in the Italian enterprise landscape.
Recently, in an exclusive interview with CIO Magazine, Paolo shared insights on his career journey, the evolution of data and AI, his approach to leadership, the secret mantra behind his success, personal hobbies and interests, future plans, words of wisdom, and much more. The following excerpts are taken from the interview.
Hi Paolo. Can you walk us through your career journey and highlight key milestones that have shaped your expertise in data and AI?
I was fortunate to attend university during a golden era—when technologies like Mobile and Cloud Computing were emerging and laying the foundation for today’s digital world. Driven by a strong sense of urgency to do impactful and hands-on work, I began my professional journey while still a student supporting the launch of new digital ventures, working as a strategy consultant, and serving as a Researcher at the Digital Innovation Observatories of Politecnico di Milano – one of Italy’s leading academic institutions.
It was during my time as a Researcher that I was first drawn to the field of Data Analytics and its first major disruption regarding Big Data. Soon after, I helped launch a Consultancy firm founded by professors and colleagues from the same Research center, focusing my efforts on building data-driven capabilities for clients. It was a pivotal time: many large companies were eager to establish internal Data and Data Science teams but lacked both organizational clarity and technical leadership to support them. This gave me the opportunity to help shape some of the earliest data organizations in Italy, including leading an end-to-end project that built what became the country’s largest analytics team within a major utility.
As demand grew, I expanded my work from strategic advisory to hands-on development of machine learning models, which quickly gained traction in the market. This momentum led me to lead the Data & AI Practice of one of the largest consulting and system integration firms in Italy and Europe. Later, I joined a younger, fast-growing company where, in early 2019, I decided to launch an AI tools division alongside our core services. That same year, in just a few months, we developed our first generative AI product – an early LLM-like solution tailored for Marketing and Campaign Automation. Looking back, that intuition was remarkably ahead of its time. The product delivered strong results despite the initial challenge of bringing such a novel, unfamiliar technology to market.
What do you love the most about your current role?
About three years ago, together with a friend and colleague, I had the pleasure of launching the Italian office of Metyis, an international firm with a unique proposition in the market. What drew me in – beyond the entrepreneurial challenge – was a radically different model from traditional consulting. At Metyis, our ambition is to build long-term partnerships, often structured as Joint Centures hosted within our Campuses. Here, we don’t simply act as consultants. Our mission is to help companies unlock and accelerate their Digital capabilities – including Data and AI – by working side by side with them.
In the early phases, we lead these ventures ourselves and deploy our own teams to deliver value. But our true goal is to scale internal capabilities, hire external talent, build mature organizations and processes, and hand the venture back to the client, transforming it into an in-house department. Put simply, we aim to make ourselves unnecessary as fast as possible. We believe that’s the only way to create real, lasting value – by making our partners truly owners of their key digital capabilities.
This approach makes me genuinely proud. It’s a model that’s hard not to appreciate if you’re a professional driven by tangible, long-term impact. Our partnerships are international in scope and allow us to break the traditional client-supplier paradigm, sitting on the same side of the table as the brands we support. It’s a powerful mix of capabilities – spanning strategy, AI development, organizational design, and talent growth.
How do you see the landscape of data and AI evolving in the next 5 years, and what opportunities or challenges do you foresee?
It’s undeniable that AI is still a field in evolution- one that, like all major technological disruptions, has yet to reach its final and most transformative acceleration. I’ll be honest: this is the kind of market phase I don’t particularly enjoy. Just as we saw during the Data Science boom, we’re now in a moment of hype where everyone claims to be an AI expert, making it incredibly difficult for companies to distinguish real expertise from empty buzzwords.
There’s clearly a widespread lack of foundational knowledge, and the marketing noise from large vendors and consulting firms is only making the picture more confusing. Take AI agents, for example – despite the hype, they don’t truly exist yet. What we have today are enhanced automation tools – far more advanced than the old RPA era – but still a long way from true, general-purpose agents.
The real challenge – and opportunity – lies in starting to experiment with these tools, understanding how to integrate them into the business, and above all, testing the organization’s ability to adapt within their evolution. What makes AI fundamentally different from past digital technologies is its unprecedented pace of development. Unlike vendor-driven tech cycles, AI isn’t stabilizing – it’s advancing too quickly for traditional reference points to hold.
In my view, the biggest acceleration is still ahead of us. It will come with a complete rethinking of the underlying models that power tools like ChatGPT or Gemini today. What we need is intelligence capable of working at a higher level – finding connections, abstracting, and creating in ways that are still uniquely human. What we’re seeing now may feel revolutionary, but it’s not. These systems are simply performing tasks they’ve been trained to do – albeit exceptionally well. The real leap is coming, and just like today’s tools, the next wave of AI will become a foundational commodity – essential to operate and compete in any industry. When that moment arrives, the real competitive advantage will lie with companies and providers who hold proprietary data – information that today’s AI models don’t access or use, but that could dramatically enhance their intelligence and deliver real market differentiation.
What skills or qualities do you look for when building a team, and how do you develop talent in the field of data and AI?
I’ve always believed that strong technical expertise must be complemented by solid business acumen. Being able to build models without understanding their real value – or without knowing how to guide domain experts in applying them – is a major trap that many, if not most, have fallen into over the years. Today, that paradox is even more striking: commercial AI tools can be used with almost no technical background, and they can even help purely business-oriented professionals write Python code they would never have managed on their own.
I believe the traditional boundaries we’ve long used to separate “roles” are quickly disappearing. We need to move toward building teams where each individual has a well-rounded skill set, with one or two sharp edges of deep expertise. Only this kind of structure will allow us to truly harness the potential of AI – by fostering teams that can understand one another, work collaboratively, and deliver real impact. For this to happen – and for individual countries to keep pace with those who move first – the evolution of education systems will be absolutely crucial.
What principles guide your leadership style, and how do you motivate your teams to drive innovation?
Looking back, it’s interesting to see how AI has long been a key element in how I motivated and inspired my teams. Managing real AI projects well before they became mainstream – and building structures that developed actual AI products comparable to the tools we all use today – was a powerful accelerator in attracting top talent and pushing them to give their best. Whether it was purely technical profiles or advisory roles seeking disruptive ways to help companies evolve, AI served as a unifying driver of ambition and purpose.
Today, however, I advocate for a more measured approach. We’re closely monitoring market developments, fully aware that only a handful of major players truly have the resources to lead the AI race. At the same time, we’re investing in upskilling our teams and expanding our business initiatives to help clients navigate this complex transition—while actively identifying unclaimed use cases and emerging opportunities where we can reapply our technical expertise in the near future. What brings us together and keeps us motivated is the desire to be a voice outside the mainstream – one that doesn’t exploit the current hype, but instead focuses on creating genuine, lasting value for our partners and clients.
Congratulations on being recognized as one of the Top 25 AI Leaders 2025. Our readers would love to know the secret mantra behind your success.
First and foremost, I want to thank everyone for this recognition. As I’ve recently mentioned elsewhere, this award – and the incredible global selection of talent behind it – offers real value to companies seeking trusted advisors in this space.
There’s no real secret behind it – just a deep passion and a genuine sense of enjoyment that makes my work feel more like a hobby than an obligation. I’m also grateful to my current company, which has allowed me to broaden my geographic horizons and connect with incredible colleagues and clients who have further enriched my professional journey.
Being an investor, what criteria do you use to evaluate startup investments, and what advice would you give to entrepreneurs looking to build successful AI-driven businesses?
Even before my interest in AI, I’ve always been passionate about innovation – and I’ve consistently sought to support, whenever possible, high-potential startups and talented entrepreneurs. As mentioned earlier, today we see “AI” everywhere – especially in startup pitches. In many cases, it’s a clear attempt to ride the hype and appear more attractive to investors, without it being clear whether the AI component is a meaningful adoption of existing technologies or a questionable in-house solution.
If we truly want to invest in something with real technical substance, a solid understanding of AI’s underlying mechanics – and of its evolving market context – is essential. Conversely, if the investment is more speculative in nature, then more than ever, the focus should be on the founders: their track record, their commercial instincts, and their network. These remain the only real differentiators in a crowded market full of overlapping ideas and technologies that are often difficult to evaluate on purely technical grounds.
Is there a particular person you are grateful for who helped get you to where you are?
When I answered the first question about the milestones in my AI journey, one person immediately came to mind: my father. Although he had little connection to technology or the kind of work I do today, he’s always had a natural instinct for innovation – and a remarkable ability to teach me the value of being pragmatic and hands-on.
I believe my passion for technology and numbers, along with my curiosity to experiment and see tangible results, can be traced back to him – and to one of his first gifts when I was very young: a Commodore 64 and a programming book that I read over and over until the pages were worn out.
What are some of your passions outside of work? What do you like to do in your time off?
Outside of work, I try first and foremost to be a good partner to Chiara, and I’m the proud father of Lorenzo. I’ve always loved sports, though I’ll admit that work commitments over the years have left me with less time to practice than I’d like.
As a family, we all share a deep love for the sea, and we escape to our seaside home whenever we can—to relax and explore new places together in our kayaks.
What are your goals and aspirations for the next phase of your career, and how do you see yourself contributing to the field of data and AI?
I’ll admit I don’t yet have a rigid or overly structured vision in terms of expectations for the future. What has always excited me the most is taking emerging topics and using AI to reshape how they’re understood and adopted. In the past, I had the opportunity to do this with the fields of neuroscience and neuromarketing, where I reimagined traditional practices through AI-powered solutions that transformed how those disciplines were applied. My hope is to replicate – and expand – experiences like that in new, unexplored domains.
Alongside this, I carry a more personal ambition. I’ve always been a bit of a contrarian when it comes to the idea that AI will take away jobs. Instead, I fully agree with those who say our children will grow up to work in roles that don’t even exist yet. In that sense, my deepest aspiration is to play a part in this evolution – to help today’s and tomorrow’s workforce truly understand AI, learn how to use it, and turn it into a tool that empowers and enhances their professional journeys.