IBM Unveils Crucial Insights on AI Sovereignty in New Study

On June 17, 2026, International Business Machines Corp (IBM) released a comprehensive study revealing the challenges enterprises face as they increasingly integrate artificial intelligence (AI) into their core business operations. Conducted by the IBM Institute for Business Value, this global study titled "The Calculus of AI Sovereignty" highlights the operational constraints that organizations encounter due to their dependencies on AI systems, calling attention to the pressing issue of AI sovereignty.

The study surveyed 1,000 senior executives from various organizations, uncovering alarming statistics about the difficulties companies face in switching AI vendors. A staggering 71% of respondents indicated that changing their primary AI vendor or model would be a significant challenge. This statistic underscores the rigid dependencies that many organizations have developed around their AI systems, potentially stifling innovation and agility.

Moreover, 68% of executives reported complications in meeting data residency and sovereignty requirements across different geographies. As global regulations around data handling become more stringent, organizations must navigate the complexities of moving AI systems and data across various environments. These challenges are intensifying the need for firms to enhance their control and oversight as AI adoption grows.

Despite the critical need for control, the study reveals a concerning lack of visibility among organizations regarding their AI dependencies. An overwhelming 91% of respondents admitted that they do not fully comprehend their dependencies across AI vendors, models, and infrastructure. This lack of understanding limits their ability to assess risks and plan for potential disruptions, which have already become a common occurrence. Surveyed leaders reported experiencing an average of six AI-related disruptions over the past two years, primarily caused by issues related to vendor services.

The ramifications of these disruptions are significant, with 81% of executives stating that a seven-day outage from a vendor would lead to severe or critical operational disruptions. This vulnerability not only risks halting business activities but also could lead to substantial financial losses.

Ana Paula Assis, IBM's Senior Vice President and Chair for EMEA and APAC, emphasized the economic stakes involved in AI governance. She stated, "AI has introduced new forms of dependency that evolve faster than traditional governance, procurement, or technology cycles were designed to handle." Assis pointed out that losing control over AI systems could lead to margin pressure, compliance risks, or outright business disruption.

The study also highlights that organizations that successfully design AI systems capable of adapting to changing conditions tend to outperform their peers. Those with advanced AI control capabilities experience significantly less downtime and can protect 55% more operating profit from AI-driven disruptions. However, only a mere 7% of surveyed organizations currently operate at this advanced level, indicating a widening gap between those who are building adaptable systems and those who remain constrained by dependency.

While 73% of organizations claim to have intentionally adopted a multi-vendor strategy for their AI environments, the reality appears to be driven more by internal and operational necessities rather than a deliberate strategic choice. Key factors influencing vendor diversity include independent business unit decisions (69%), geographic requirements (69%), and legacy complexities stemming from mergers and acquisitions (57%).

The study not only identifies the challenges associated with AI dependencies but also provides a roadmap for senior executives aiming to build flexible, resilient, and sovereign AI systems. The full study is accessible for those interested in exploring these insights further.

As AI continues to permeate various sectors, IBM's study serves as a crucial reminder of the importance of AI sovereignty in today's business landscape. The findings underscore the need for organizations to enhance their governance around AI systems to mitigate risk and ensure operational resilience. As the stakes grow higher, businesses must adapt to maintain their competitive edge in an increasingly complex technological environment.