What McKinsey's State of AI 2026 Means for Italian Business
Italian companies are adopting AI faster than ever. The harder part is turning that adoption into money.
Italian businesses have been closing the AI gap quickly. According to Istat, the share of Italian companies with at least 10 employees using at least one AI technology doubled in a single year, from 8.2% in 2024 to 16.4% in 2025. In 2023 it was just 5%. The Politecnico di Milano's Artificial Intelligence Observatory puts the size of the Italian AI market at €1.8 billion in 2025, up 50% from the year before.
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| The author: working as Digital Learning Coach in Italy |
Adoption, though, is only the first step. McKinsey's latest global survey, The State of AI in 2026: On the Road to ROI, is built on 1,719 respondents in 97 countries. Its central message matters to every Italian board: AI use is spreading quickly, but bottom-line impact is not keeping up.
Below are the report's main findings and what they mean for Italy's economy, which runs on manufacturing and SMEs.
1. Large companies are moving ahead, and Italy's SMEs risk falling behind
McKinsey finds that the gap between large and small companies is widening. Among organisations with more than $1 billion in annual revenue, the share scaling AI agents rose from 27% to 40% in one year. Among smaller organisations it stayed flat at 22%. Overall, 54% of large-company respondents say AI is scaling across their enterprise, compared with one-third of smaller firms.
This should worry Italy, where SMEs are the backbone of the economy. Istat's data show the same split at home: 53.1% of Italian companies with more than 250 employees use AI, against 15.7% of SMEs. The national average of 16.4% is also below the EU-27 figure of 20%, and there is a clear North–South divide (19.3% in the North-West against 12.2% in the South).
Diagram 1: The size gap, globally and in Italy
SCALING AI AGENTS (McKinsey global survey, 2026)
Large orgs (≥$1B revenue) ████████████████████ 40% (27% in 2025)
Smaller orgs ███████████ 22% (22% in 2025)
USING ANY AI TECHNOLOGY (Istat, Italy, 2025)
Large firms (250+ empl.) ██████████████████████████▌ 53.1%
SMEs (10–249 empl.) ███████▊ 15.7%
Italy average ████████▏ 16.4%
EU-27 average ██████████ 20.0%
Note: the two sources measure different things (scaling agents vs. any AI use). The pattern of large firms pulling ahead is the same in both.
What this means for Italy: AI could widen the productivity gap between Italian large firms and the SMEs in their supply chains. Industrial districts, trade associations and supply-chain leaders can help here by sharing infrastructure, skills and proven use cases with smaller partners.
2. "Build vs buy" is being rethought, which fits Italian industrial culture
One of the newest findings is how coding agents are changing technology budgets. About two in ten organisations are scaling software coding agents, rising to 31% at large enterprises. Nearly a third of respondents (32%) say their organisations decided against buying at least one software product or feature because they could build it in-house with agentic coding tools. Among AI high performers the figure is nearly half.
Italian business is known for customisation, craft and solutions designed around specific needs, so this trend suits it well. The Politecnico di Milano Observatory finds that 77% of the Italian AI market is made up of custom projects built for individual clients. It also notes that larger companies in mature sectors such as banking, insurance and energy have built internal AI teams and now rely less on outside vendors.
Senior partner Lieven Van der Veken describes the change in mindset:
"Until recently, many leaders assumed that AI was beyond the capabilities of their own technology teams, and that moving quickly meant securing the right external partnership. Now, the tone is changing. Leaders are asking what their organizations need to build AI tools themselves."
This does not mean Italian companies should build everything themselves. The point is to choose deliberately what to buy, what to build, and which internal skills are needed to integrate and scale what works. For Italy's software and system-integrator ecosystem, it also signals a change in what clients will expect: less packaged licensing, more support for clients' own development.
3. Individuals gain, companies wait
This is the report's most striking finding. 80% of respondents say AI has improved their personal productivity, and about half say it helps them make better decisions and learn new skills. Yet only 37% report any positive impact on EBIT, essentially the same as last year. "AI high performers", companies that attribute at least 5% of EBIT to AI and describe its value as "significant", make up only about 6% of respondents, also unchanged.
Diagram 2: The gap between individual gains and enterprise impact
0% 25% 50% 75% 100%
|---------|---------|---------|---------|
Individuals: "AI improves my productivity" ████████████████████████████████ 80%
Individuals: "AI helps me decide better" ████████████████████ 50%
Organisations: any EBIT impact from AI ██████████████▊ 37%
Organisations: AI high performers ██▍ 6%
◄──── INDIVIDUAL LEVEL ────► ◄──── ENTERPRISE LEVEL ────►
The gap is an operating-model problem
Senior partner Dan Tinkoff sums it up:
"The opportunity for business leaders is to harness the energy created by growing employee literacy and to establish an operating model that enables them to lead the end-to-end reimagining of workflows in their areas of responsibility at speed and at scale."
Italian workers are already building AI skills. The Observatory reports that job postings requiring AI skills grew 93% in 2025. Gains made by individuals still have to be turned into gains for the organisation through processes, governance and measurement. Two points in the report deserve attention:
- Middle managers and individual contributors feel more strain. 47% report at least one negative effect, such as stress, mental fatigue or being overwhelmed by AI outputs, compared with 31% of executives. Italian leaders should not assume that their own positive experience is shared further down the organisation.
- The financial impact appears at the function level. Cost reductions are most often reported in supply chain management, service operations and manufacturing, which are core areas for Made in Italy. Revenue gains are most often reported in marketing and sales, followed by product development. The functions where AI pays off are the ones that drive Italian competitiveness.
4. AI isn't "too cheap to meter"
As use grows, costs are rising too. One in five respondents says AI operating costs, including tokens, have limited their AI use. Per-token prices are falling, but token consumption, especially for agentic coding and complex reasoning tasks, is growing even faster. High performers report cost constraints on coding agents three times as often as others (18% vs. 6%), a sign of how heavily they use them.
Even so, investment keeps rising. 60% of respondents expect their organisation to increase AI investment next year, and 28% already spend more than 10% of their ICT budget on AI. Pharma and medical products, insurance and financial institutions are the most bullish sectors, and all three are important in Italy.
For Italian CFOs, many of whom run tightly controlled budgets, the lesson is to treat "tokenomics" as a design constraint from the start. Monitor usage, match the model to the task (not every job needs a frontier model), and manage general-purpose tools such as chatbots as a standard business cost, like office software.
5. Jobs: the predicted cuts did not happen
The report helps put Italy's public debate about AI and jobs in perspective. Last year, 32% of respondents expected AI to reduce their organisation's headcount within 12 months. In reality, only 14% report an AI-related workforce decline, and two-thirds saw little or no change.
Diagram 3: Workforce expectations vs. reality
Share of respondents citing an AI-driven DECREASE in total headcount
2025 expectation (next 12 months) ████████████████ 32%
2026 actual outcome (past 12 months) ███████ 14% ◄ less than half
2026 expectation (next 12 months) ███████████████████▌ 39%
"Little or no change" expected in 2026: 43%
"AI makes me anxious about my career": 13%
Expectations are rising again: 39% now expect cuts, mostly in service operations and supply chain. With Italy's demographic decline and serious skills shortages, AI could do more to fill gaps than to replace workers. That depends on companies doing serious strategic workforce planning, which is one of the practices that sets high performers apart.
6. The high performers' playbook
What do the 6% who turn AI into real financial results do differently? McKinsey identifies a consistent approach:
- Bigger ambitions. About 80% pursue efficiency, like everyone else, but most also pursue growth and innovation. They are 3.3 times more likely to aim for fundamental business transformation within three years.
- They redesign workflows instead of adding AI on top. Nearly three-quarters have fundamentally redesigned workflows (up from 55%), against a quarter of other companies.
- Committed leadership. They are twice as likely to have senior leaders who visibly own AI initiatives, and twice as likely to have defined processes for measuring impact.
- Larger investments. They are more than twice as likely to spend over 15% of the ICT budget on AI.
- Broader use, with more risk management. They are more than three times as likely to scale agents in most functions, and they work harder to mitigate risks such as cybersecurity threats and unauthorised agent actions. This matters in Europe as the EU AI Act takes effect.
Associate partner Tara Balakrishnan names what is often the real obstacle:
"This is no simple task, which helps explain why adoption tends to move more slowly than the technology does: The limiting factor is increasingly the organization's ability to absorb change."
Five questions for Italian business leaders
- Are we redesigning processes, or just adding tools? Pick one end-to-end process, such as order-to-cash, after-sales service or production planning, and rebuild it around AI.
- Do we measure impact? Without defined KPIs, AI stays a cost item and never becomes a value lever.
- What is our build-vs-buy strategy? Check which software renewals could be replaced by internal development with coding agents.
- Do we govern AI costs? Set up token and compute monitoring before usage takes off.
- Are we bringing our supply chain along? Italian competitiveness depends on whole networks. If large firms move ahead and their SME partners don't, the whole system loses.
Conclusion
The McKinsey survey shows that companies' confidence in AI is growing faster than the financial returns they can attribute to it. For Italy this is both a warning and an opportunity. The warning is that buying tools does not create value on its own. The opportunity is that the qualities Italian businesses are known for, including deep process knowledge, a culture of customisation, and close-knit districts and supply chains, are exactly what it takes to redesign workflows and build tailored solutions.
The winners will not be the companies with the most pilots. They will be the ones that turn individual productivity gains into lasting results at the company level.
Sources: McKinsey & Company, "The State of AI in 2026: On the Road to ROI" (August 2026, global survey of 1,719 respondents); Istat, "Imprese e ICT – Anno 2025"; Osservatorio Artificial Intelligence, Politecnico di Milano (2026). The McKinsey data are global and not specific to Italy.
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