Artificial Intelligence Market: Evolution and Opportunities in Italy for Startups

The Artificial Intelligence market in Italy is accelerating, transforming business models and corporate strategies. In 2025, growth reached significant levels, driven by investments, widespread adoption in large companies, and a growing availability of ready-to-use solutions. In this article we explore key data, governance, skills, and opportunities for startups aiming to enter this dynamic landscape.

The market context in numbers

In 2025 the Italian AI market reached about 1.8 billion euros, with a 50% growth compared to 2024. 46% of the market is generated by GenAI solutions or hybrid projects, the remaining 54% by Machine Learning projects. There are approximately 1,010 Italian companies recorded that offer AI solutions and services and 135 startups funded in the last five years.

Adoption, licenses and business models

In 2025 71% of large Italian companies have started at least one AI project, with a significant share of ready-to-use solutions. 84% of large companies hold Generative AI licenses. For SMEs the diffusion is lower: about 9% use paid tools and another 9% free tools. Companies are attracted by the low cost of access and ease of use, but they are aware that banning its use could give rise to Shadow AI and loss of control.

Governance and compliance

A small minority of companies is truly ready in AI governance and compliance: among large enterprises, barely 9% have a structured AI governance, with clear responsibilities and alignment to ethical objectives. A substantial share, 54%, is moving to structure centralized governance. Analyzing the obligations under the AI Act, more than one in two companies has launched awareness initiatives, but only 15% are running a structured adaptation project integrated with other regulations.

Benefits of AI for workers

Ready-to-use Generative AI tools are offering a wide range of applications; among large companies that adopt them, 54% attempt to measure benefits and, in many cases, employee feedback is used. Only 11% conduct periodic and structured monitoring. Workers using AI report significant time savings in certain tasks, and a sizable share admits to being able to perform activities they previously could not. Moreover, demand for AI skills grew rapidly: in 2025, job postings requiring AI skills increased by 93%, with 76% of postings for highly qualified white-collar profiles including AI competencies.

Demand for skills and required profiles

Analyzing over 17 million job postings published between 2019 and 2025, The Observatory found that about 44,000 positions out of 3.2 million require AI skills in 2025, up 93% from the previous year. White-collar high-skilled roles are among the most AI-driven: 76% of postings for these roles require AI skills. AI is also present in 27% of postings for Chief Human Resources Officer and in 12% of postings for Chief Marketing Officer. These indicators show growing demand for figures capable of leading organizational and productive transformation.

Use and impact on the business model

Companies that have launched AI projects have shown positive impacts on their business model, with greater focus on value proposition, customer relationships, and operating architecture. However, about one in three report difficulties in estimating cost-benefit ratios in advance. The adoption of GenAI has embraced ready-to-use solutions, but requires governance to avoid risks and create real value, not just productivity indicators.

Outlook for startups and strategic decisions

For startups, operating in this context means taking advantage of a growing market that rewards rapid, modular, data-driven solutions. Opportunities are greater in sectors where digital transformation is already advanced, such as healthcare and fintech, but demand will also rise among SMEs and the public administration, thanks to document automation and textual analysis solutions. Companies are looking at GenAI tools and data exploration and automation platforms, with clear attention to ethical guidelines and usage. Startups will have to differentiate themselves with internal governance, transparency, and clear measurement of benefits, avoiding Shadow AI practices and demonstrating concrete impacts.

Paragraph for debate and reflections

The debate around AI in Italy involves various perspectives and critical reflections. On one hand, AI promises a productivity boost and new competitive opportunities: access to GenAI tools lowers entry barriers, enables rapid prototyping, and allows companies to test new ideas at low cost. This opens space for startups in traditionally conservative sectors, offering hybrid business models and data-driven services. Widespread adoption could spur new skills, data quality production, and shared infrastructures that foster collaboration among companies, universities, and research centers, as well as new market outlets for vertical solutions. On the other hand, significant risks remain. Insufficient and fragmented governance can lead to control, privacy, and ethics issues. Shadow AI, reliance on third-party providers, and biases in models are recurring topics that require clear regulations and shared standards. The European AI Act imposes literacy and compliance obligations that require resources and time, and many entities, especially SMEs, need accompanying tools and training. Some critics warn that rapid adoption could create competitive imbalances, with large firms able to define governance and measurements more effectively while small players struggle to align. In this context, a long-term strategy that integrates governance, data quality, ethical responsibility, and clear measurement of benefits is essential. A hybrid approach, combining internal processes with pilot projects guided by responsible AI use, could offer the best middle ground: it enables controlled experimentation, reduces risk, and supports organizational learning. It is also crucial to invest in advanced training and talent development to prevent skill drain and ensure that companies not only access new technologies but can integrate them with domain expertise. In summary, AI represents a major opportunity for economic and organizational transformation, but success depends on balancing speed, governance, ethics, and literacy. Companies that build gradual, measurable, and responsible adoption paths will lead the technology-driven transformation in the coming decade.

Concrete conclusion: opportunities and essential steps

In short, the Artificial Intelligence market in Italy is accelerating and offers real opportunities for startups and companies, provided they carefully plan governance, skills development, and value metrics. An effective path combines GenAI tools and data exploration solutions with clear governance, widespread literacy, and targeted investments in training. For those about to undertake or expand AI projects, the practical guidance is to start with a progressive, data-driven adoption plan, define governance roles from the outset, and continuously measure benefits, avoiding shortcuts and non-traceable practices. Moving toward an AI-driven transformation requires a collaborative ecosystem among businesses, public bodies, and research centers, capable of creating sustainable value over time.

Fonte osservatori.net