The figure that sums up Italy’s position in the AI economy better than any analysis is this: in 2025, venture capital invested in start-ups and technology in Italy reached €1.4 billion.
In the same year, the United Kingdom saw 120 billion invested.
France and Germany, around 50 billion each.
Italy ranks tenth in Europe by overall volume and third from last for per-capita investment: 127 euros per inhabitant. A structural gap that has produced the consequences we can see today in our economy, our development and our prospects in AI, the technology of the future and the turning point of the years ahead.
A delay measured in decades of missed choices.
The state of adoption: the real numbers
The picture that emerges from official sources is more nuanced than the public debate suggests.
In 2024 only 8.2% of Italian companies with at least 10 employees had adopted AI technologies, against a European average of 13.5%. In 2025 the situation improved, but unevenly. Among large companies adoption reached 53.1%. Among SMEs it stands at just 15.7%.
The most worrying data point, however, is the trajectory.
The gap in intensity of use between large companies and SMEs went from 20 percentage points in 2023 to 37 in 2025. The divide, then, is widening. AI is not acting as a levelling factor: it is amplifying existing organisational differences.
70% of Italian companies still have no defined AI strategy. Among those that do, the plan is often run by IT with minimal involvement from top management. It is a governance issue.
Italy’s (non-)infrastructure
AI adoption depends on the infrastructure that the will of Italian companies can rely on.
Unfortunately, however, Italy carries an infrastructure deficit that predates AI by twenty years.
Connectivity, data centres, computing capacity distributed across the country: all of these require multi-year investment and cannot be built in response to a single technological wave.
For a point of reference: Alphabet has announced Capex of between 175 and 185 billion dollars for 2026, almost double the 91.4 billion invested in 2025, largely earmarked for data centres and computing infrastructure. Amazon has announced investments of up to 200 billion in the same year. These are the figures of the global hyperscalers: an indication of what it means to build the infrastructure needed to compete in the AI economy.
Italy has no publicly available aggregate figure for industrial Capex specifically allocated to AI.
That in itself is an answer.
Clearly, a country that does not measure how much it invests in a strategic technology has not yet decided to treat it as one.
The European comparison that hurts most
The TEHA Global Innosystem Index 2026 ranks Italy 31st out of 49 countries analysed for overall innovation capacity, behind Singapore, Israel, the United Kingdom and many other European countries. The assessment measures the ability to turn research into economic value, to attract and retain talent, and to build productive ecosystems capable of scaling.
Italy excels in the quality of its scientific research but suffers from structural delays in investment and in developing STEM skills, and fails to fully turn academic excellence into economic value.
This is the Italian paradox: widespread expertise, a system unable to make the most of it.
The ISTAT 2026 Report is explicit: in 2025 Italian GDP exceeded its 2007 level by just 1.9%. Over the same period, France, Germany and Spain recorded growth of close to 20%.
Three structural causes have been identified: delayed investment in intangibles, a fragmented productive base, and limited capacity for innovation linked to human capital skills. AI aggravates all three.
How long would it take to catch up?
This is the hardest question. And it must be asked honestly.
There is no official, verifiable projection of how long Italy would need to close the gap with the leading European countries in AI adoption. Estimates are fragmented, produced by parties with differing interests, and rarely comparable with one another.
What we can say from the available data is this. The European target set by the Commission is for 75% of businesses with at least 10 employees to adopt AI technologies by 2030. Italy currently stands at 14.7% among SMEs and 53.1% among large enterprises. Reaching 75% among SMEs within five years would mean quintupling the current adoption rate in a segment that accounts for 99% of Italy’s productive base.
It is possible. It is not likely without systemic change in the three variables that matter: infrastructure investment, availability of skills, and corporate governance of innovation.
The Minsait-Ambrosetti study estimates that structured adoption of AI in Italian businesses could translate into an overall productivity gain of €115 billion. It is an estimate, not a forecast. But it indicates the order of magnitude of what is at stake.
The real bottleneck
The data converge on a point the public debate tends to ignore: Italy’s problem is the organisational capacity to understand AI, govern it and integrate it into processes.
A one-year increase in the average age of workers is associated with a 0.3 percentage point reduction in the probability of product innovation and 0.7 points in that of process innovation. In 2023, over 60% of Italian industrial and service businesses had an average workforce age of 42 or above.
The technology is available. The models are accessible. The tools exist. What is missing lies in the human and organisational infrastructure that should be using it.
But a word of caution. Let us bear this in mind: a company without an AI strategy has less a technology problem than a governance problem. And governance is built through decisions, processes and responsibilities clearly distributed among those who lead the company.
Italy’s lag on AI is a lag of vision. And lags of vision cost more than infrastructural ones, because they are not easily measured, cannot be recovered through an extraordinary spending plan, and give no warning signs until the gap has already become structural.
Italy will therefore only resolve these structural and strategic difficulties when those leading it understand that AI is a strategic variable that changes the way companies, the country and the entire national vision can compete and create value.
For many Italian companies, that moment is already long gone.
New Connections (FAQ)
Why does the gap between large enterprises and SMEs in AI adoption keep widening?
Because the starting points are too different. A large company already has someone to delegate exploration to: a CTO, an IT team, a structured technology budget. When a new technology arrives, someone studies it as part of their job. Italian SMEs, which make up 99% of the country’s business base, usually lack that structure. And AI does not close this gap: it widens it, because it rewards those who already have the organisational foundations to use it well.
Is Italy’s problem one of investment or of organisational culture?
Both, but the debate always looks at the first and ignores the second. People discuss European funds, capex, Transizione 5.0. Meanwhile, 70% of Italian companies still have no AI strategy — not for lack of money, but because nobody with strategic authority has taken ownership of the question. I have seen companies buy expensive licences and hand them to IT without senior leadership really knowing why. Without direction, technology is just a cost.
Where can an average Italian company realistically start?
By understanding where you stand now. Open ChatGPT and ask about your company. Search for your name on LinkedIn and Google. What you see is what anyone trying to understand who you are sees: client, partner, competitor. If there is inconsistency or absence, that is the first problem to solve. Then: identify the two or three processes where AI delivers a genuinely better result than the existing alternative, measure it, and scale only what stands up to measurement. Governance does not require an extraordinary budget. It requires someone to take responsibility for the direction.