EMEA Sovereignty Report

Enterprise AI is becoming core infrastructure, embedded in customer operations, software development, analytics and increasingly autonomous workflows. That raises a question beyond choosing the best model today: what happens when providers, regulations and technology change? The EMEA Enterprise AI Sovereignty Index 2026 measures how much freedom enterprises really have to change course.

Download the report to see where confidence in recovery and the reality of switching diverge, which dependencies are hardest to replace, and how leaders can design AI that keeps working as the ecosystem evolves.

The survey behind the index

The index is based on a survey of 228 enterprise leaders across the EMEA region, from organizations with 500 to more than 5,000 employees. Respondents include C-level executives, vice presidents and directors, and all hold decision-making authority over technology or AI strategy. Responses were analyzed across provider dependency, architectural portability, recovery confidence and sovereignty posture.

54% of enterprises expect to recover a critical AI capability within 30 days, but only 8% could switch providers without re-engineering

More than 80% of respondents believe they could restore a critical capability within three months. The report calls this the Illusion of Resilience: the belief that having an alternative provider means having an alternative operating capability. The model is one part of the solution, and around it sit applications, prompts, agents, data pipelines, security controls, integrations and operating processes. Asked how much of the solution would have to change to replace the model or provider behind their most business-critical AI capability, respondents answered:

Nine in 10 enterprises have delayed, redesigned or stopped AI initiatives because of sovereignty issues

Only 10% of respondents say their AI initiatives have not been affected by questions of data control, regulation, jurisdiction or provider dependency, and 21% say more than a quarter of their initiatives have been affected. Sovereignty is not simply a compliance issue. It affects AI velocity. When these questions are addressed late, organizations redesign architectures, revisit vendors and repeat governance reviews. When they are addressed at the start, sovereignty moves upstream from a compliance decision made at deployment to an architecture decision made during design, and control and speed stop trading off against each other.

85% of enterprises want access to better-performing AI and plan to manage the dependency, not avoid it

Offered a choice between stronger AI performance and economics on one side and greater technology dependency on the other, most leaders did not walk away from AI. They chose to manage dependency through contractual protection, architectural replaceability or acceptance. What they want is optionality within the AI ecosystem: access to better models and the pace of innovation, along with an answer to what happens when today's best option is no longer tomorrow's best option.

61% see excessive dependency as at least as risky as moving too slowly, yet only 17% design for replaceability

The report calls this the optionality gap. Executive concern has moved faster than enterprise architecture. The principle that guides AI architecture most often is access to the best-performing AI capabilities (32%), followed by cost and operational efficiency (22%) and security, regulatory and compliance requirements (21%). Designing for replaceability of models or providers guides 11% of enterprises, and maintaining multiple viable options guides 6%.

Cloud and infrastructure, not the model, is the dependency enterprises expect to be hardest to replace

Lock-in involves more than foundation models. Asked which dependency would be hardest to replace, enterprises answered:

Being multi-model does not make an enterprise sovereign. Only 9% say they maintain viable alternatives for critical dependencies, so sovereignty has to cover architecture, data, cloud, applications, skills and the ability to move the business capability as a whole.

AI dependency is becoming enterprise risk, and accountability still sits mostly with technology leaders

As AI supports customer service, fraud detection, pricing and operations, a failure reaches customer experience, revenue and decision-making well beyond the technology organization. Yet 38% of enterprises say accountability for keeping critical AI capabilities running sits with technology leadership, and only 6% say it is shared and clearly defined.

Sovereignty is measured on four dimensions: control, portability, resilience and strategic autonomy

Where data is stored or where a provider is headquartered is only part of the picture. An organization can meet data residency requirements and still be locked into a provider it cannot replace. The index measures enterprises on four dimensions:

The report goes on to sort enterprises into four groups on the sovereignty index, from dependent to sovereign, and sets out what separates them.