Italy’s financial sector embraces AI cautiously amid risks and slow market shift

Italy’s financial sector is gradually adopting AI, mainly to improve efficiency in internal operations like data analysis, fraud detection and customer support, while core market activities remain largely unchanged. Wider adoption is held back by regulatory uncertainty, data challenges and skill gaps, even as authorities promote safe innovation and stronger oversight.

Artificial intelligence is no longer a distant concept for Italy's financial sector. It is already being used across banks, insurers and investment firms, though often in ways that are less visible to customers. A major OECD report, developed with the European Commission and Italian authorities such as Banca d'Italia, CONSOB and IVASS, shows that the country's financial system is gradually embracing AI while still moving cautiously.

Around 40 percent of financial institutions in Italy now use AI in their daily operations. Adoption is strongest in banking and insurance, while financial market players such as asset managers are catching up more slowly. Even so, most firms are still experimenting rather than fully relying on AI, testing new tools before rolling them out widely.

Where AI is making a difference

Today, AI is mostly helping financial firms run more efficiently. It is widely used for analysing data, generating reports, detecting fraud, checking compliance and supporting customer service through chatbots. These uses are practical, relatively low-risk and deliver quick results.

Firms report clear benefits. AI helps cut costs, speed up routine tasks and improve decision-making. It can process large volumes of information faster than humans and identify patterns that might otherwise go unnoticed. However, these gains are mainly seen in back-office operations rather than in high-value financial market activities.

Why core markets remain cautious

Despite the progress, AI has not yet transformed how financial markets operate. Its use in areas like trading, investment decisions or settlement processes remains limited. Institutions are careful about relying on systems that can be complex and difficult to fully understand.

Another reason is trust. Financial decisions often involve high stakes, and firms prefer to keep humans in control. Most AI systems in use today still require human oversight, meaning they support decisions rather than make them independently. Fully automated systems are rare and mostly limited to small or low-risk tasks.

Dependence on big tech and growing risks

A major trend highlighted in the report is the reliance on third-party providers. Most Italian financial firms depend on external technology companies for cloud services and AI tools. This approach allows quick access to advanced systems without building them internally.

However, this dependence raises concerns. Relying on a few large providers creates risks around data security, system resilience and market concentration. If something goes wrong at the provider level, it could affect many firms at once. This makes strong governance and oversight essential.

Inside firms, governance structures are still developing. There is no single approach to managing AI risks. Companies typically combine existing frameworks such as cybersecurity, data protection and risk management. At the same time, challenges like explaining how AI makes decisions and protecting systems from cyber threats are still being addressed.

Regulation, skills and data: the real barriers

The biggest obstacles to wider AI adoption are not just technical. Regulation plays a major role. Many firms say they face uncertainty about how new rules, especially the EU AI Act, will apply alongside existing financial regulations. This lack of clarity makes it harder to plan long-term investments.

Other barriers are equally important. There is a shortage of skilled professionals who understand both finance and AI. Many firms struggle to hire and retain the right talent. Data is another challenge. AI systems need large amounts of high-quality data, but accessing and managing this data can be difficult and expensive.

A system in transition

Italy's financial authorities are actively responding. They are monitoring AI use, developing supervisory tools and supporting innovation through initiatives like regulatory sandboxes and the Milano Hub. These efforts aim to balance innovation with safety.

Overall, the report shows a sector in transition. AI is already improving efficiency and reshaping internal operations, but its full impact on financial markets is still ahead. The next phase will depend on clearer regulation, better data access and stronger skills. For now, Italian finance is moving forward carefully, building the foundations for a more AI-driven future.