In a rapidly evolving economic and political landscape, science and technology are key levers for business competitiveness. Italian firms, which are part of an extensive network of small and medium-sized enterprises, have shown great creativity and resilience in difficult conditions: this ability to adapt can serve as a strategic launchpad to address the changes currently taking place, starting with the technological revolution.
The first challenge in this sphere concerns Italy’s innovation system, a system that features both light and shade. With 1.38% of GDP invested in research and development, compared with a European average of 2.26%, the country suffers from a structural lag aggravated by insufficient public-private collaboration. The sector employs 520,000 people, less than half the numbers of Italy’s main European competitors, while their average salary is 53,000 euros, compared with 90,000 euros in Germany. This gap is fueling the brain drain: 97,000 graduates have left Italy in the past decade.
Notwithstanding these limitations, Italian research shows no lack of quality: the country’s citation impact exceeds the world average by 26%; a full 13.5% of publications in the global top ten are Italian. This performance is even more surprising considering that Italy has one of the world’s oldest populations, with projections to 2050 suggesting that the population of over-65s will be three times larger than that of the younger generations. In addition, other countries offer greater rewards for researchers.
When discussing technology the impact of artificial intelligence – which is increasingly present in the daily lives of businesses and individuals – cannot be underestimated. Its unprecedented speed and its ability to encompass such diverse domains – from economic and production systems to the personal sphere – make the AI revolution very different from the technological revolutions of the past. While previous revolutions unfolded over decades, allowing their economic, political and social impacts to be addressed gradually, AI poses much greater challenges over an extremely compressed time horizon. The real question, then, is no longer whether AI should be adopted, but whether its adoption can be governed.
The country’s digital infrastructure is developing: fiber coverage will be completed by the end of 2027, while the numbers of data centers and supercomputers are growing. Yet the ability to exploit Italy’s growing digital infrastructure still varies notably with company size. Data for Milan’s vast metropolitan area, one of Europe’s principal manufacturing clusters, suggest that 60% of large companies have initiated AI pilot projects, compared with 15% of medium-sized enterprises and just 7% of small ones. This gap does not depend on costs – which are relatively affordable – but on businesses’ in-house skills and their ability to rethink organizational processes. Indeed, the transformation triggered by AI is primarily organizational: first a clear strategy is needed, with technology following.
Against this background, the huge opportunity offered by the adoption of AI should not be underestimated: exploiting the huge pool of industrial data deriving from Italy’s manufacturing sector means increasing productivity and generating wealth and well-being. Projects have already been initiated in this field to create common, interoperable standards and develop them in a protected environment by fostering “coopetition” and sharing data in a protected associative environment to train AI.
Italy must build on its strengths, both in advanced sectors such as robotics and pharmaceuticals and in its historical ability to develop applications for new technologies. However, the country suffers from a lack of national champions in technology sectors. To remedy this, it needs to move on from the current approach, based on research incentives, and encourage the creation of national spheres of excellence. Actors with the necessary soundness and strength also have the ability to foster technology transfer. The German model of Fraunhofer institutes – which generates three euros in tax revenue for every euro invested – should be considered a best practice in addressing the problem of access to research for Italian SMEs. Other European experiences point to the importance of a clear and stable framework of incentives for businesses, one that is not subordinated to annual budgetary contingencies.
The challenge, however, is not just economic, but also cultural. While at the global level most of the population views algorithms and new technologies as part of everyday life, Italy’s profile can be described as pragmatic and wary, set within the framework of a European attitude that is more deeply reflective and strongly based on a culture of regulation.
For the public to better understand and accept AI – an enabling factor in the adoption of technology in society and the economy – education and training must be improved. Italy needs initiatives to remedy information asymmetries among citizens. Public interventions must be channeled along three axes. The first concerns infrastructure and extensive connectivity to encourage the use of technology. The second entails establishing a political-institutional narrative that presents AI as a collective project. And the last, but no less important, axis involves strengthening educational capital and social trust. The challenge for Italy is to democratize AI advocates by leaving behind the opportunism that seems to characterize the current situation. The country’s very organizational and social culture must change to some degree. Only then will Italy be able to govern, rather than merely submit to, this transformation.