AI is already in your future

 

AI adoption in Europe and Italy since 2022, and what it means for your career

Lecture delivered 20th of October 2026

Lecture for the undergraduate degree in Artificial Intelligence Management

Duration: about 60 minutes 50 of lecture and 10 of discussion)

Short link: https://bit.ly/OPTI_class20ottobre2026

Slides: https://app.decktopus.com/nano/6094779/present?code=LktCyw

Future of work Italian version: https://bit.ly/DrAlbert_futurodellevoro

Jensen Huang interview: https://bit.ly/interview_huang

Learning objectives

By the end of the lecture you will be able to:

• explain why generative AI was adopted first by individuals and only later by organizations;
• read European and Italian AI adoption data critically, distinguishing between use and value created;
• place Italy’s position in a historical and European perspective;
• use a structured framework to assess the return on investment (ROI) of AI under conditions of high uncertainty;
• discuss the advantages and limits of the European AI Act;
• define a concrete plan to develop AI skills and demonstrate them to an employer.

Outline

Part	Topic	Time
1	Introduction: a technology you already have in your pocket	5 min
2	Four facts about generative AI	12 min
3	Europe since 2022: where does Italy stand?	10 min
4	Italy: rapid growth, large gaps, little measurement	10 min
5	Why Europe is lagging	7 min
6	Your role in the AI economy	6 min
7	Conclusion and a two-week action	2 min
Q&A	Questions and discussion	10 min

Minimal glossary

Before we begin, let us fix some terms we will use often.

• Generative AI: systems that produce new content (text, images, code, audio) from an instruction given by the user, called a prompt [2].
• LLM (Large Language Model): a large-scale language model, such as ChatGPT, Gemini, Claude or DeepSeek.
• Benchmark: a standardized test used to compare the performance of models.
• AI agent: a system that plans, uses external tools and carries out multi-step tasks with a degree of autonomy [8].
• Open-weight model: a model whose “weights” (the learned parameters) are published and can be downloaded, run locally and modified [14].
• API: an interface that lets other software use a paid model without owning it.
• SMEs: small and medium-sized enterprises, meaning those with 10–249 employees in Istat statistics [17].
  
  

L'IA sta già assumendo: voi dove vi collocate?

 

L'adozione dell'intelligenza artificiale in Europa e in Italia dal 2022, e cosa significa per la vostra carriera

Lezione per il corso di laurea triennale in Management dell'intelligenza artificiale
Durata: circa 60 minuti (50 di lezione e 10 di discussione)

Short link: https://bit.ly/OPTI_lezione20ottobre2026

Slides: https://app.decktopus.com/nano/6094779/present?code=LktCyw

Versione futuro del lavoro: https://bit.ly/DrAlbert_futurodellevoro

Intervista Jensen Huang: https://bit.ly/interview_huang

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Obiettivi di apprendimento

Alla fine della lezione sarete in grado di:

1. spiegare perché l'IA generativa è stata adottata prima dalle persone e solo dopo dalle organizzazioni;
2. leggere in modo critico i dati europei e italiani sull'adozione dell'IA, distinguendo tra uso e valore creato;
3. collocare la posizione dell'Italia in una prospettiva storica ed europea;
4. usare uno schema strutturato per valutare il ritorno sugli investimenti (ROI) in IA in condizioni di forte incertezza;
5. discutere vantaggi e limiti dell'AI Act europeo;
6. definire un piano concreto per sviluppare competenze sull'IA e dimostrarle a un datore di lavoro.

AI in Business in Italy - From Pilots to Profit

 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.

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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.

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.

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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.

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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.

LLMs in Business the Huang Interview - CEO & Founder of NVIDIA

 

What the Huang Interview Shows, How Ready Organizations Are, and What to Expect Next Year

In a long conversation on The Ezra Klein Show on 23 September 2026, Nvidia CEO Jensen Huang made the case that AI has moved from promise to everyday use. This post sums up what he said about how large language models (LLMs) work in business, checks how ready organisations actually are, and predicts how fast things will change over the next year.