Mateus Morato Fantini is Chief AI and Innovation Officer at Informa PLC, where he leads AI strategy and implementation across one of the world’s largest B2B information businesses.
Starting as a self-taught computer technician in Brazil, Mateus worked through software development and architecture roles while studying part-time. Before moving to Switzerland in 2010, he led architecture at Latin America’s largest car rental operation.
In Switzerland, he joined Swisscom’s ALL-IP transformation, then TIBCO’s Quantum Leap Innovation team, designing cloud and IoT solutions that won industry recognition.
But it was at Informa where he found the scale and complexity that define his current work.
Since 2013, Mateus has held several senior roles across Informa PLC, including President of IIRIS, the company’s enterprise data platform. His work has spanned revenue-generating platforms like Informa Connect CORE, Taylor & Francis digital eBooks and data monetisation products such as LeadInsights.
Most recently, he co-led Project Gemini, which became Elysia—Informa’s enterprise AI platform now supporting more than 16,000 employees and commercial use cases.
Mateus holds an MBA and a master’s degree in strategy and innovation. He completed AI and Data Strategy and Implementation programs at IMD Business School, MIT and was recognised among Europe’s Top 100 leaders in data and AI by DataIQ in 2025.
His perspective is shaped by working in federated organisations: successful AI transformation isn’t about centralising control. It’s about creating alignment, building trust and enabling co-creation.
As a data and AI leader, which traits and skills do you think matter most, and which of those have been most influential for you in your current position?
“I’d put systems thinking at the top—the practical ability to see how technology, data, people, incentives and governance fit together. You can build technically brilliant solutions that go nowhere because you missed one of these pieces.
“At Informa, three things have made the biggest difference:
“First, knowing when to ship. We launched Elysia with core features and iterated based on actual usage. ‘Good enough now’ often beats ‘perfect later’ because you learn what actually matters from real users. We’re now releasing AI features fortnightly.
“Second, building trust across functions. Getting legal, security and business teams aligned on AI was about working transparently and showing them we could make AI both powerful and responsible. Our partnerships with AWS and Microsoft were strategic choices that de-risked innovation.
“Third, resilience. Transformation surfaces friction: political, cultural, technical, financial. Someone needs to absorb that pressure while keeping the team focused on outcomes.”
Reflecting on your career, what is one non-traditional piece of advice (outside of technical skills) you would give to an aspiring data or AI leader aiming for the C-suite?
“I once read Mintzberg quoting Lorenz: ‘Every man gets a narrower and narrower field of knowledge in which he must be an expert… The specialist knows more and more about less and less and finally knows everything about nothing.’
“That’s a real risk in AI right now. I’ve deliberately kept my hands-on skills current, but there’s a point of diminishing returns. Deep expertise is increasingly a luxury for academics and researchers.
“I’ve also invested heavily in management, strategy and organisational design because Mintzberg warned of the opposite risk: managers knowing ‘less and less about more and more until finally they know nothing about everything.’
“Here’s the thing: conceptual management without technical understanding struggles to deliver sustainable transformation. But pure technical expertise alone won’t drive adoption or buy-in.
“So my advice: don’t become an expert in an increasingly narrow field, but don’t abandon technical depth either. You need to be credible in the engineering room and compelling in the boardroom. That balance is what makes the difference between leaders who execute and those who just talk strategy.”