AI is changing how we work, how we produce, how we decide, and how we learn.
When we talk about the future of work, we usually start with technology: artificial intelligence, automation, data, platforms. And rightly so. These are powerful forces.
But the real question is: which institutions will help us govern this transformation?
Because new technologies alone are not enough. What matters is whether we can build the right contexts for those technologies to become quality jobs, new businesses, growth, and social cohesion.
From this perspective, universities have an enormous responsibility.
Not only as places where knowledge is produced and transmitted, but as places that connect those who know, those who experiment, those who invest, and those who build.
In simple terms, the university must become a point of connection.
And this is crucial. Because today, the problem is not a lack of knowledge. Research exists. Companies exist. Talented young people exist. Real needs exist. What is often missing is the place where these lines truly meet.
This is where initiatives such as Start Attractor can become a piece of the solution: not by replacing universities, research, or businesses, but by helping them connect earlier, better, and in a more operational way.
There is research, but it does not always meet business early enough.
There is talent, but it does not always find enough opportunities to experiment.
There is a strong need for innovation, but there is not always an interface capable of translating that need into concrete collaboration. This is why the issue is urgent. Much more urgent than it sometimes appears.
According to the World Economic Forum’s Future of Jobs Report 2025, by 2030, 22% of jobs are expected to be significantly transformed. The report estimates 170 million new roles will be created, while 92 million roles will be displaced. It also highlights that 39% of workers’ core skills are expected to change by 2030, and that 63% of employers identify skills gaps as the main barrier to business transformation.
In other words, the challenge is not only the speed at which innovation and AI are advancing. The real challenge is whether we are preparing people and organizations to use them well.
Technology has already entered companies.
The question is: who is truly ready to govern it?
AI, by itself, is not the change. AI is like electricity. If it enters a room but is not connected to the system, nothing really changes. It remains a powerful possibility, but not yet a real transformation. But when AI enters processes, organizations, skills, and decision-making, everything changes. It changes how we work. It changes how we produce. It changes how we decide. It changes how we learn.
This is why teaching people how to use a new tool is not enough. We need to redesign the contexts in which that tool can generate value. In the age of AI, education can no longer be limited to transferring content. Access to information is now everywhere. Value increasingly lies in judgment, critical thinking, collaboration, hybrid skills, lifelong learning, and networks.
In other words, it is no longer enough to know more. We need to think better. We need to connect better. We need to decide better. This changes the role of the university.
If universities are to become true connectors between knowledge and reality, three pillars become fundamental: education, technology transfer, and entrepreneurship.
The first pillar is education.
Educating people does not only mean teaching a discipline. It means preparing people to navigate complexity.
People who can work with AI without delegating their judgment to AI.
People who can speak with technicians, but also with those who lead organizations.
People who can transform knowledge into solutions.
Education, in this sense, is no longer a phase that ends with a degree. It becomes a continuous process that accompanies the transformation of people, companies, and territories.
This is also part of the role that Start Attractor can play: supporting a culture of lifelong learning, upskilling, and reskilling, so that innovation does not remain abstract but becomes a capability shared across the ecosystem.
The second pillar is technology transfer
Technology transfer is not a bureaucratic step that begins at the end, when research has already been completed.
Technology transfer works when it becomes a strategy: a continuous translation between different worlds.
Between laboratory and factory.
Between researchers and managers.
Between those who develop a solution and those who have a real problem to solve.
The key is not only to produce knowledge.
The key is to build the conditions for that knowledge to be understood, tested, adopted, and scaled.
Technology transfer must be designed as part of a broader strategy that includes research, companies, talent, capital, and territories.
This is where structures such as Start Attractor can make a difference: not by replacing research or business, but by helping them speak to each other earlier, better, and in a more operational way.
Start Attractor is not the whole solution. But it is a piece of the solution: a connector that helps transform knowledge into collaboration, and collaboration into impact.
The third pillar is entrepreneurship. And entrepreneurship does not only mean startups.
Entrepreneurship is a widespread mindset. It means seeing an opportunity where others see only a constraint. It means validating a need. It means building a value proposition. It means bringing together different skills. It means taking responsibility for bringing an idea into the real world. This ability is also essential for researchers. For managers. For public administrations. For anyone who wants to transform knowledge into impact. In this sense, entrepreneurship is not only about creating new companies. It is about creating the conditions for ideas to move, evolve, and become useful.
A university should not limit itself to generating brilliant ideas. It should contribute to creating the conditions for those ideas to find a trajectory toward society. For a team to be formed. For a problem to be validated. For a prototype to meet a market. For research not to remain closed inside a scientific article, but to become a concrete possibility for the territory.
What emerges is a new idea of university.
A university that trains more flexible and adaptive people.
A university that accelerates the transition from research to application.
A university that spreads an entrepreneurial culture as a capacity for activation.
A university that helps its territory not merely adapt to change, but shape it.
For years, we thought the role of the university was to prepare people to enter a world that was already built. Today, that world is no longer already built. It is being rewritten before our eyes. And so the role of the university changes. Not only to prepare people for the future, but to help people, companies, and cities build the future.
Because the future, in the end, does not reward those who predict it best.
It rewards those who organize themselves first to build it.