‘This is why the EU must create a system to compete’

European collaboration in the technological field is “the only possible solution” to make the EU capable of competing on a global scale. It is urgent to “break barriers, harmonize legislation, try to ensure that there can be more European champions”. Thus the CEO of Engineering, Maximo Ibarra, in a conversation with Adnkronos on the sidelines of the Comolake conference.

In the race to develop artificial intelligence, American champions have a clear advantage. Also because they boast much more important resources than those of European players, explains the CEO of the Italian group. Therefore, despite the creativity of European companies – “certainly with an asset that should not be underestimated” – it becomes necessary to create the conditions to reach the critical mass necessary to compete.

European competitiveness also passes through the integration of training, with important repercussions also on investments in research and development or research and innovation, explains Ibarra. According to the CEO, programs such as those launched post-pandemic such as the Pnrr “are fundamental” because “they help institutions collaborate with companies and vice versa, also from a training point of view”.

When the resource of skills is scarce – and it is scarce all over the world, he points out – it is clear that we need to bring those of companies together in a win-win collaboration. “As Engineering we have proposed and in fact already set up an alliance for technological Italy with another player in the sector. This is an alliance open to all, with the aim of working together on effective technology solutions in dialogue with institutions and public administration.

The role of the EU

Such a system requires a European Union “that must think as if it were a group of countries with zero barriers regarding technology and training, infrastructure and rules”, explains Ibarra.

His appeal to the EU institutions is to promote legislative harmonization, but also to balance the need to regulate and innovate, aspects that “must go hand in hand”. Such a balance could allow EU companies to “lead in the world compared to other geographies, because we have both elements”.

To guarantee European competitiveness we also need to rely on the availability of quantity and quality data, recalls the CEO. Like the other sectors, greater harmonization is needed here too: “if a linguistic model is built in Italy it would be advisable to also be able to have access to the data generated in other European countries, and vice versa”. More data to continue training the models, not necessarily in the language of the country of origin, which “could facilitate the creation of generative AI operators that have the characteristics to be able to compete with other geographical areas”.

Also pay attention to the high cost of electricity, which puts European companies at a disadvantage compared to foreign competitors. Some large US companies address rising electricity consumption with long-term contracts with nuclear power plants. In the EU, however, “a lot of work needs to be done” on guaranteeing low-cost energy to maintain computational infrastructures, data centers and servers that are able to respond to the needs of the continent. Only then will it be possible to think about a European technological ecosystem “that can easily compete with Asian or American giants”.

In Italy and elsewhere the adoption of AI systems is already established, with the stabilization of some applications generating an average increase in productivity between 1 and 5%. A figure that can “easily double” over the next year and a half. Such figures are already found in some specific cases and not only in Italy, continues Ibarra. Furthermore, estimates on the development of AI are often underestimated in the positive sense, in the sense that times are shortened, he adds.

No slowdown in sight because “the areas of application are very clear”, especially in some industrial sectors such as in the manufacturing world, where there is “a very intensive use of machine learning tools, therefore basically predictive tools”, explains the CEO .

Other sectors are slower to implement AI to improve products, even if the automation of repetitive processes “is starting to be in the DNA of almost all companies in all sectors, from retail to fashion to manufacturing”. The innovations today are in the field of improving customer service, for example through new generation chatbots, continues Ibarra.

The combined adoption of AI and digital twins is also growing as they “begin to work more and more together” and reinforce each other. The example is the field of medicine, where “public health is investing a lot” and Engineering manages the national telemedicine platform created for Agenas. The group’s CEO predicts that this acceleration “will give very positive surprises in the next two years”.

“Engineering has existed for more than forty years and has accumulated an information set of all the industries in which we operate, which are practically all those present in Italy and beyond. Having accumulated that information wealth, we have pre-trained our platform from a business-to-business perspective with the most relevant open industry information. Not only from the point of view of production processes, from a business point of view, but also from a legislative, normative and regulatory point of view,” says Ibarra.

The result: for a company to equip itself with such a model is equivalent to equipping itself with a wealth of data that it would hardly have been able to build on its own. This allows it to accelerate a series of processes, continues the CEO: “understand insights, understand use cases, essentially find solutions to automate or become more capable in the field of predictive analysis”. In essence, Engineering’s lesson is that companies “need platforms pre-trained on their specific industry needs.”