From the adoption of AI to value creation: the new challenge facing Italian businesses
Artificial intelligence has moved beyond the stage of theoretical exploration to take a firm place at the heart of companies’ strategic agendas. In Italia, the figures confirm a marked acceleration: according to data from the Artificial Intelligence Observatory at the Politecnico di Milano, the national AI market reached a value of 1.8 billion euros in 2025, marking a 50 per cent increase compared with the previous twelve months. This momentum is clearly reflected in the development plans of major industrial and service groups, where 71 per cent of organisations have already launched at least one dedicated project.
The real dividing line, however, no longer lies in the launch of new use cases or trials, but in the ability to industrialise artificial intelligence, transforming promising initiatives into governed, secure and scalable business capabilities, integrated into core processes and measured against business outcomes. Whilst the era of proof-of-concept projects can be said to be well and truly underway, the transition to enterprise-wide deployment now represents the real bottleneck in the production system. Barely one in five large organisations makes pervasive use of artificial intelligence across multiple business functions. The vast majority of initiatives remain confined to experimental silos, failing to produce a tangible and systematic impact on productivity, time-to-market and the quality of decision-making processes.
But the challenge is not merely to scale up an increasing number of use cases. AI is bringing about a paradigm shift in the very way in which businesses design and execute their processes. Viewing it as a series of one-off applications to be grafted onto existing activities risks severely limiting its potential. The real leap in value occurs when organisations move beyond the logic of automating individual tasks and rethink end-to-end processes, combining people, data, artificial intelligence and, increasingly, agent-based systems.
Customer service, finance, procurement, supply chain, marketing and IT functions can thus evolve not through a series of isolated efficiency improvements, but through a structural transformation of the way in which work is organised, carried out and governed. It is in the shift from individual use cases to the redesign of processes that AI can realise its greatest economic potential. Success is no longer measured solely by the number of solutions implemented or the hours of work saved, but by the impact on the company’s key performance indicators: productivity, cost-to-serve, time-to-market, quality and speed of decision-making, revenue growth and profit margins. The aim is to translate technological potential into sustainable economic results, ultimately generating a measurable contribution to EBITDA and value creation.
Bridging this gap requires a shift in perspective when it comes to investment too: technology alone is not enough. Innovation gains value when it forms part of a clear industrial vision, supported by rigorous governance models, cybersecurity safeguards, appropriate skills and targeted investment in change management. It is no coincidence that in-house skills remain one of the main obstacles: almost 60 per cent of organisations that have assessed AI without subsequently adopting it identify the shortage of qualified personnel as one of the key obstacles.
