A new global study by the IBM Institute for Business Value, published on June 17, 2026, finds that as enterprises embed AI deeper into core business operations, most surveyed organizations remain locked into AI systems they cannot easily change—reinforcing the growing importance of AI sovereignty to maintain business continuity and performance. Titled The Calculus of AI Sovereignty, the study is based on insights from 1,000 senior executives responsible for AI, data, technology, or related enterprise capabilities across 16 countries and 17 industries.

Key Findings: Dependency and Lack of Visibility

The study highlights a widespread inability among enterprises to adapt or switch AI systems, creating significant operational constraints. A majority of surveyed executives report challenges across multiple dimensions of AI control, as summarized below:

Surveyed leaders report an average of six AI-related disruptions over the past two years, largely driven by vendor services. Respondents also cite unexpected changes across the AI ecosystem, including price increases, usage restrictions, model deprecations, and performance degradation.

The Cost of Lost Control

IBM Senior Vice President and Chair, EMEA and APAC, Ana Paula Assis, said in the study foreword: "AI has introduced new forms of dependency that evolve faster than traditional governance, procurement, or technology cycles were designed to handle. That is why AI sovereignty has become one of the most defining leadership issues of this moment. The stakes are no longer technical; they are economic. Any loss of control can translate directly into margin pressure, compliance exposure, or outright business disruption."

Performance Gap Between Leaders and Laggards

The study identifies a significant performance divide between organizations that have built advanced AI control capabilities and those that have not. Key findings on this gap include:

• Organizations with the most advanced AI control capabilities see less AI downtime and protect 55% more operating profit from AI-driven disruptions.
• Only 7% of surveyed organizations operate at this advanced level, signaling a widening gap between those building adaptable AI systems and those constrained by dependency.
• 72% of surveyed executives say they would accept a 20% cost increase to maintain AI vendors if it improved strategic flexibility.

Multi-Vendor Environments: Strategy vs. Reality

Most surveyed organizations (73%) describe their AI environments as intentionally multi-vendor. However, vendor diversity in practice appears to be driven less by deliberate strategy and more by internal and operational realities. The leading drivers cited by respondents are:

• Independent business unit decisions and geographic necessity, each cited by 69% of respondents.
• Legacy complexity—reflecting mergers, acquisitions, and historical decisions—cited by 57% of respondents.

Study Methodology

The IBM Institute for Business Value, in collaboration with Oxford Economics, conducted a global survey between February and April 2026 to examine how organizations structure control across the AI stack and how these choices relate to resilience, performance, and operating economics. The study is based on responses from 1,000 senior executives across 16 countries and 17 industries. Additional analysis identified distinct AI control profiles by segmenting organizations based on how they structure control across data, models, infrastructure, and applications.

IBM and ServiceNow have expanded their partnership to develop joint solutions that modernize legacy systems and enable AI-ready data governance. The collaboration integrates IBM's software solutions with the ServiceNow AI Platform to help enterprises break through outdated systems and put their data to work for AI. The joint solutions aim to enable autonomous IT operations, allowing the world's largest enterprises to unlock the transformative value of agentic AI.

Decades of deeply interconnected legacy systems are the biggest barrier to moving fast on AI. IBM and ServiceNow are addressing this by helping organizations evolve existing systems rather than replace them, run AI on any model they choose, and unlock the full depth of their enterprise data. The partnership combines IBM's AI, data, and automation capabilities with the ServiceNow AI Platform.

"Most enterprises have the ambition to deploy agentic AI, but lack the foundation to run it at scale," said John Aisien, senior vice president and general manager, central product management, security & risk at ServiceNow. "IBM brings the tooling to modernize the systems and extend ServiceNow's data capabilities. ServiceNow provides the platform to put that data to work across every workflow in the business. Together, we're helping enterprises move from AI ambition to real, scalable outcomes."

"AI adoption at scale requires more than access to models. It requires rethinking the systems, data and workflows that support them," said Raj Datta, vice president of ISV and AI partnerships at IBM. "Together with ServiceNow, we're building an open, flexible foundation for AI that can scale across operations and deliver real business value."

The collaboration will create new solutions for customers across three key areas:

These joint solutions are expected to be available in the second half of 2026.