What does Human Development mean when artificial intelligence becomes a geopolitical, economic, and democratic imperative rather than a technological option? In this conversation, we explore why the true competitive edge now lies in the ability of people, organizations, and countries to understand, govern, and operationalize AI. From cultural resistance in legacy industries to Europe’s race for digital sovereignty, and Italy’s challenge to scale cooperation and retain talent, this interview outlines the shifts required to navigate a world where technology defines structural advantage.
Today we’re surfing with Marco Becca, Director of IFAB (International Foundation Big Data and Artificial Intelligence for Human Development).
For me, Human Development today starts from a simple but crucial idea: technology is no longer a gadget, an optional add-on, or merely a productivity tool for companies. It has become something far more strategic. It plays a geopolitical role, an economic role, and increasingly, a democratic one. A country, a continent— and on a smaller scale, a company or an individual—that does not understand, use, or possess these technologies is at a structural disadvantage. AI is no longer optional.
This is why Human Development, in my view, means enabling people, organizations, and entire ecosystems to govern technology— to develop it, use it, and benefit from it.
Human Development therefore also means culture and education. We, at IFAB, work both with companies and with civil society. As a foundation, we collaborate extensively with schools—particularly technical institutes and vocational programs—because many young people risk missing the “AI train.” In the past, you could join a company and learn everything on the job. With AI, this is no longer guaranteed. If students do not encounter AI during their education, they may arrive in the workforce already behind.
So, in short, Human Development today means enabling society to shape technology through production, governance, culture, and education.
From my experience—as CEO of a digital subsidiary in gaming and later as General Manager in insurance—the biggest barrier is culture. It’s the “we’ve always done it this way” mindset. Budget can be a constraint, but in many organizations the true obstacle isn’t money: it’s resistance to change.
In one of my previous role in a major gaming and entertainment company, I also acted as Innovation Manager. Even simple changes—digitizing paper processes or testing blockchain—met huge resistance. Not because the tech was complex, but because changing habits is hard.
With AI, this challenge grows. AI is deeply transformative. It reshapes how people work, organize their day, analyze data, and communicate. Its impact forces a rethink of fundamental workflows. In established companies, where processes have existed for decades, this cultural inertia is even stronger.
To handle this, organizations must invest in education, training, and awareness. People need to clearly understand what AI can and cannot do—avoiding both “AI can do everything” and “AI is too fast for me.” Reducing anxiety and encouraging a positive approach to innovation is essential.
Finance matters, of course—but unless you’re a hyper-profitable giant, it’s rarely the real issue. Culture comes first.
When discussing AI, I prefer to speak from a European vantage point. On a global scale, Europe is undeniably behind the United States and China—both in scale and in speed of acceleration. But the game is still at an early stage. Some races may already be lost but the real value of AI lies in the data that companies possess.
Large Language Models can write, read, and generate content—these are, metaphorically, the “elementary school” capabilities. The real competitive edge appears when AI is combined with proprietary industrial or enterprise data. And this is precisely where Europe risks having the largest gap.
There are two reasons:
We should distinguish two layers of AI: model creation and training, and deployment and operationalization.
Europe is making progress on the first layer. Infrastructure is strengthening, and data initiatives are moving in the right direction. But deployment cannot be led by the public sector alone. Private organizations must play a central role—not to replace hyperscalers, but to avoid full dependency on them.
On the operational side, Europe is further behind. Large “giga-centers” will only come online at the end of next year. The private sector needs to invest, organize, and build these capabilities; the EU can co-fund, but it cannot lead on its own.
When it comes to centralization versus decentralization, the reality is that both models will coexist. Large compute centers will remain inherently centralized, simply because physics demands it: they need huge amounts of energy, industrial-scale cooling, and robust power infrastructure.
At the same time, edge computing will expand dramatically. Many data sources cannot be moved efficiently, and in many applications latency is critical. Processing needs to happen close to where data is generated.
The future, therefore, is a hybrid model: centralized, large-scale compute hubs—including AI factories and giga-factories— paired with a vast layer of edge-AI systems, deployed directly where data originates.
Italy’s challenge is not to “show muscles” by claiming the largest computer center. Our real opportunity lies in learning to operate effectively as part of a network.
I see three priorities for Italy:
Marco Becca is the Director of IFAB (International Foundation Big Data and Artificial Intelligence for Human Development), where he drives the strategic intersection of technology and societal progress.
With a foundation in Electronic Engineering and an MBA from SDA Bocconi, his extensive career began in strategy management consulting. He later held various C-level roles across the Telco, Insurance, and Gaming sectors, developing a deep understanding of corporate digital transformation.
In the last decade, Marco has become a key player in the Italian innovation ecosystem as an active Business Angel (member of Italian Angels For Growth since 2012) and co-founder of FoolFarm, a pioneering Venture Builder focused on AI and blockchain technologies. His diverse expertise makes him a leading voice on how big data and AI can be responsibly leveraged for human progress.