We are first in Europe for AI adoption.
And I know, that alone is a remarkable figure: far from what one might expect. Yet it is true: McKinsey’s ConsumerWise survey records it for the first quarter of 2026. 74% of Italian consumers have used AI tools in the last three weeks to research, compare products and plan purchases. Ahead of the United Kingdom (67%), Germany (66%), France (63%) and Spain (59%). When it comes to shopping, the Italian consumer is the most familiar with AI in Europe.
And yet those same Italians are the lowest users of AI in the workplace across the entire continent. Just 26%. The United Kingdom, France, Germany, the Netherlands and Sweden all rank above us.
74% adoption as consumers. 26% adoption when it comes to work.
The same country, the same quarter, the same tool. Two worlds that do not talk to each other. And two figures that reveal a fracture that is hard to ignore: Italians are learning to use AI faster as individuals than as organisations.
The problem is not curiosity
For months, Italy’s lag in adopting artificial intelligence has been explained by a supposed cultural resistance to technology. Consumer data make this reading less convincing.
When access is simple, the benefit immediate and the decision individual, Italians experiment. In companies the opposite happens. Adoption has to pass through processes, responsibilities, tools, training, security, data and internal rules. At that point, everything changes.
Istat data show this too. In 2025, 16.4% of Italian companies with at least ten employees used at least one AI technology, double the 8.2% of the previous year. Growth is strong but unevenly distributed: among large companies adoption reaches 53.1%, while among SMEs it stops at 15.7%.
A management issue
Yet not all companies behave in the same way. And the difference lies entirely in management.
Where employers encourage the use of AI, provide adequate tools and invest in training, adoption grows.
We can therefore infer that the gap between 74% and 26% does not describe a population unable to use artificial intelligence, but rather organisations where that same capability has yet to find clear processes, permissions or objectives.
And this is where a technological lag can turn into a competitive lag.
The customer may be ahead of the company
There is another consequence, perhaps even more pressing for brands.
If a growing share of consumers use AI to research before buying, the purchase journey changes before many companies have even introduced AI into their own processes. Customers can query ChatGPT, Gemini or other systems about the product, compare alternatives and form an opinion while the company is still reasoning in terms of funnels designed for traditional search.
This creates a new paradox: an organisation can lag behind in adopting AI internally while, at the same time, depending on consumers who use it to decide whether to choose it.
The first consequence concerns visibility. Being found on Google still matters, but there is growing value in being understood, cited and accurately represented by generative systems as well.
The second concerns governance. If employees already know these tools and are starting to use them of their own accord, banning or ignoring them does not eliminate their use. It may simply make it invisible, increasing the risk of uncontrolled data sharing, unverified outputs and parallel processes.
The third concerns competitive advantage. Italian companies need not wait for the market to learn how to use AI. The market has already started.
They need to catch up with it.
New Connections (FAQ)
Why does Italy lead AI adoption in shopping despite having less developed digital infrastructure than the United Kingdom and Germany?
The most likely answer is behavioural, not infrastructural. Italian consumers have historically carried out extensive pre-purchase research, including in physical form, and pay close attention to value for money, which lends itself well to AI comparison tools. Easy access to tools such as ChatGPT via smartphone, with no need for corporate infrastructure, lowers the barrier to entry for the individual consumer. Consumer adoption does not depend on companies: it depends on the smartphone and on a willingness to experiment that the data clearly highlight.
What does it mean in practice for an Italian brand to become ‘agent-ready’?
It means that brand information must be accessible, accurate and well structured in the formats AI systems use to answer users’ questions. An AI agent searching for “the best Italian extra virgin olive oil under 20 euros” must find consistent, verified and up-to-date information about the brand. GEO, Generative Engine Optimization, is to AI systems what SEO has been to traditional search engines. Brands that do not manage it are simply ignored by agents, regardless of the quality of their product.
Where should an Italian company whose employees already use AI begin?
By making visible what is probably already happening. Before buying new tools, the company should map which systems are being used, for which activities, with which data and without which controls. From this snapshot can come authorised tools, an AI Policy, training, levels of Human Oversight and criteria that vary according to the risk of individual use cases. It is one of the central points of Bliss’s AI Governance approach: governing real adoption before chasing the ideal one. When spontaneous use is turned into a shared system of rules, responsibilities and objectives, the familiarity people have already developed with AI can become an organisational capability instead of remaining mere shadow AI.
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