DGS interprets the Artificial Intelligence Observatory 2025: the Artificial Intelligence market in Italy is growing rapidly, but organizational maturity remains lower than the pace of investment growth.

What emerges from the Artificial Intelligence Observatory 2025?

The final conference of the Artificial Intelligence Observatory of the Politecnico di Milano mapped the state of AI in Italy in 2025. The data show a market in strong growth, but also a still evident gap between the spread of solutions and their integration into organizations’ operating models.

How much is the Italian Artificial Intelligence market worth in 2025?

In 2025, the Italian Artificial Intelligence market reaches 1.8 billion euros, with +50% growth compared to 2024 and a three-year CAGR of +54%. Generative AI accounts for 46% of total value and grows by +60% year over year.

This confirms that AI is no longer confined to narrow experiments, but has become a structural part of investment strategies. However, market size alone is not enough to describe the real maturity level of companies.

How are large Italian companies adopting AI?

Adoption is broad, but not yet fully pervasive. The Observatory’s overview shows that many companies have started experimenting with Artificial Intelligence, while a much smaller share has managed to roll it out extensively across different functions and business processes.

• 71% of large Italian companies have launched at least one AI project.
• Only 21% report significant diffusion across multiple business functions.

The transition from the project phase to full operational integration is therefore still incomplete. To achieve widespread adoption, organizations need evolved operating models, data governance, and adequate internal skills.

Why is Generative AI spreading so quickly?

Generative AI has gained traction quickly because it is easy to activate and requires limited initial investment. According to the Observatory, <strong>84%</strong> of large companies use ready-to-use Generative AI tools.

This ease of access encourages diffusion, but it also raises a problem of value measurement. Only a limited share of organizations systematically evaluates the benefits generated, and just 9% declare fully integrated AI governance.

The risk is that AI remains a tool for individual productivity, without becoming a concrete driver of change. For this reason, adoption is not only a technological issue, but also one of people, trust, and skills.

What is Shadow AI and why is it a critical issue?

Shadow AI refers to the ungoverned use of Artificial Intelligence tools. In the Observatory’s overview, only 19% of workers use exclusively official company platforms, a sign that makes governance a central issue.

This scenario calls for clear rules, defined priorities, and decision models supported by human-in-the-loop supervision, in order to ensure security, compliance, and traceability. For DGS, the convergence between AI and cybersecurity is an essential enabling factor.

Governance, therefore, is not only risk control: it is also a strategic lever to build trust, ensure responsible and ethical use of technologies, and maintain alignment with regulations and organizational responsibilities.

What is the phase shift for organizations?

According to the Observatory data, the current phase marks the shift from hype to integration. After the initial expansion and enthusiasm for Generative AI, organizations are called to consolidate sustainable and measurable adoption models.

The point is not to “do AI,” but to adopt it in a structured way, integrating it into core processes, information systems, and decision-making mechanisms. This requires defining business-aligned priorities and use cases, integrating company data, clear governance, defined responsibilities, and impact measurement.

The need becomes even more relevant with the evolution toward agentic models, where AI agents do not just generate content but act on business processes, making decisions and executing actions.

What is DGS’s point of view?

For DGS, the value of Artificial Intelligence emerges when technology, data, and people converge into an integrated model capable of producing reliable and measurable results. The difference lies in organizations’ ability to govern adoption, integrate AI into core processes, and define measurable KPIs, clear governance rules, and operational guardrails with human-in-the-loop supervision.

“Many companies are investing in AI, but often struggle to turn these efforts into concrete results, because the real obstacle is not technological but organizational” – Vincenzo Fiengo, Co-CEO DGS."

DGS acts as a Data &amp; AI partner focused on concrete transformation. With over 300 specialized professionals and more than 600 completed projects, it supports organizations in building value-driven adoption roadmaps, translating PoCs and ready-to-use solutions into real, scalable, and secure operational impact.

How can AI be integrated into business processes sustainably?

The goal is to integrate AI into existing processes, ensuring security and compliance while defining sustainable governance models. Only in this way is it possible to measure results in terms of efficiency, quality, and operational impact.

From this perspective, Artificial Intelligence becomes a strategic ally for companies rather than an investment in itself. The combination of integration, control, and measurement makes it possible to move from an experimental phase to an adoption that truly generates value.

Where can the press release and full report be consulted?

To learn more about the results of the Artificial Intelligence Observatory 2025, you can consult the press release or access the full report.