AI is already operational in most Italian organizations: candidate screening, risk analysis, and algorithms integrated into management software. These systems process sensitive data, influence critical decisions, and, in most cases, are not governed by anyone.

The problem is not adoption itself. It is adopting AI without knowing who controls the data, which systems fall under European regulations, or which provider operational continuity depends on. This last point is not theoretical: in June 2026, one of the most powerful models on the market, Claude Fable, was deactivated globally within a few hours due to a government directive, leaving those who had built processes and products on it stranded. This is an example of what it means to depend on AI you do not control.

Three fronts are converging to make 2026 a moment unlike any before. The regulatory front: the EU AI Act becomes fully applicable for high-risk systems on August 2, 2026, with obligations for documentation, traceability, and human oversight, and fines of up to 35 million euros or 7% of global turnover. The point many organizations have not yet understood is that it also applies to systems already in production, not just to those developing AI. The geopolitical and strategic fronts complete the picture: dependence on external infrastructures and models transfers part of the organization’s decision-making power to third parties.

This is the theme of our white paper “Sovereign AI 2026 Report”, which addresses the full picture:

• What “sovereign AI” means for an organization, and why the distinction between data residency and data sovereignty is decisive.
• Where they are exposed: SMEs, large companies, and Public Administration, each with different risks and intervention priorities.
• How to move from an inventory of existing AI systems to an architecture that guarantees control, compliance, and continuity over time.

Includes a self-assessment tool, a map of 2024-2027 regulatory deadlines, and a four-phase method applicable to organizations of different sizes and sectors.