IBM Study: Limited Control and Rising Dependencies Leave Enterprises Exposed in the Age of AI

IBM (NYSE: IBM) released a global study on AI sovereignty and enterprise risk.

Rhea-AI Summary

IBM (NYSE: IBM) released a global study on AI sovereignty and enterprise risk. Among 1,000 executives, 71% say switching their primary AI vendor or model is difficult and 68% struggle with data residency and sovereignty rules. 91% do not fully understand dependencies across AI vendors, models and infrastructure, after averaging six AI‑related disruptions in two years. 81% say a seven‑day vendor outage would cause severe or critical disruption. Organizations with the most advanced AI control capabilities protect 55% more operating profit from AI‑driven disruptions, yet only 7% reach this level. 72% would accept a 20% cost increase to maintain AI vendors if it improved strategic flexibility.

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News Market Reaction – IBM

On Jun 17, the day this news came out, IBM closed 3.12% below the previous close.

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Key Figures

Challenging data rules: 68% of surveyed executives AI dependency visibility gap: 91% of respondents Vendor switch difficulty: 71% of respondents +5 more

Challenging data rules

68% of surveyed executives

Say meeting data residency and sovereignty requirements is challenging

AI dependency visibility gap

91% of respondents

Report not fully understanding AI dependencies across vendors, models, infrastructure

Vendor switch difficulty

71% of respondents

Say switching primary AI vendor or model would be difficult

AI-related disruptions

6 disruptions

Average AI-related disruptions per organization over past two years

Severe impact outage risk

81% of respondents

Say a seven-day AI vendor outage would cause severe or critical disruption

Advanced control protection

55% more operating profit

Protected from AI-driven disruptions by organizations with most advanced AI control

Highest control adopters

7% of organizations

Operate at most advanced AI control capability level

Survey scope

1,000 senior executives

Global survey across 16 countries and 17 industries (Feb–Apr 2026)

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Key Terms

data residency, data sovereignty, ai sovereignty, operating profit, +1 more

5 terms

data residency regulatory

"68% of surveyed executives say meeting data residency and sovereignty requirements..."

Data residency describes the country or region where a company stores and processes its digital information, shaped by local laws and technical choices. Think of it like deciding which filing cabinet in which country holds a company’s important papers — that choice affects legal obligations, privacy protections, costs and how easily the company can move or share information. Investors watch data residency because it can create regulatory risk, compliance costs and constraints on expansion or cloud strategy.

data sovereignty regulatory

"68% of surveyed executives say meeting data residency and sovereignty requirements..."

Data sovereignty is the principle that digital information is subject to the laws and control of the country or entity where it is stored or processed. For investors, it matters because where data lives affects a company's legal obligations, costs, ability to sell services across borders, and exposure to government access or restrictions — like owning a house that must follow the rules of the town it sits in.

ai sovereignty technical

"reinforcing the growing importance of AI sovereignty to maintain business continuity..."

AI sovereignty means a government or organization having effective control over the collection, storage, processing and rules governing artificial intelligence systems and the data they use. For investors, it matters because it shapes where companies can operate, which vendors they can use, and what costs or regulatory hurdles they face—similar to the difference between owning your home versus renting under strict landlord rules.

operating profit financial

"capabilities protect more than half of their operating profit from AI-driven disruptions"

Operating profit is the amount of money a company makes from its core business activities after subtracting the costs directly related to running those activities, such as wages and supplies. It shows how efficiently a company is generating profit from its main operations, serving as a key indicator for investors to assess its financial health and profitability before considering other expenses like taxes or interest.

ai stack technical

"examine how organizations structure control across the AI stack and how these choices..."

AI stack is the layered set of technologies — including computing hardware, data storage, model software, developer tools and support services — that together enable creation and operation of artificial intelligence applications. Like the foundation, framing and utilities of a building, the quality and completeness of an AI stack determine how well AI products perform, how cheaply they scale and how defensible a company’s AI offerings are, making it a key factor for investors assessing long‑term value and risk.

AI-generated analysis. How Rhea-AI works. Not financial advice.

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• 68% of surveyed executives say meeting data residency and sovereignty requirements across geographies is challenging
• Nearly all (91%) respondents report not fully understanding their AI dependencies across vendors, models, and infrastructure
• Organizations with the most advanced AI control capabilities protect more than half of their operating profit from AI-driven disruptions

ARMONK, N.Y., June 17, 2026 /PRNewswire/ -- A new global study by the IBM (NYSE: IBM) Institute for Business Value 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.

Based on insights from 1,000 senior executives, The Calculus of AI Sovereignty study* reveals that 71% of respondents say switching their primary AI vendor or model would be difficult, highlighting significant operational constraints. Additionally, 68% of surveyed executives say meeting data residency and sovereignty requirements across geographies is challenging, creating complexity in moving AI systems or data across environments. These dynamics point to growing pressure on organizations to strengthen control and oversight as AI adoption and compliance requirements expand.

While the need for control is intensifying, most organizations still lack the visibility required to act on it: 91% of those surveyed say they don't fully understand their organization's dependencies across AI vendors, models and infrastructure, limiting the ability to assess risk and plan for disruption. Surveyed leaders report an average of six AI-related disruptions over the past two years, largely driven by vendor services, yet 81% say a seven-day vendor outage would still cause severe or critical disruption, effectively halting operations.

Respondents also cite unexpected changes across the AI ecosystem, including price increases, usage restrictions, model deprecations, and performance degradation. These findings underscore the challenges enterprises face in managing AI dependencies.

Ana Paula Assis, IBM Senior Vice President and Chair, EMEA and APAC, 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."

According to the study, organizations that design AI systems to adapt data, models and infrastructure as conditions change – a core element of AI sovereignty – are outperforming peers:

• Analysis shows that organizations with the most advanced AI control capabilities see less AI downtime and protect 55% more operating profit from AI-driven disruptions.
• Yet, only a minority of the organizations surveyed (7%) operate at this 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.

Most surveyed organizations (73%) describe their AI environments as intentionally multi-‑vendor, yet vendor diversity in practice appears to be driven less by deliberate strategy and more by internal and operational realities¹:

• Independent business unit decisions (69%) and geographic necessity (69%) emerge as the leading drivers.
• Legacy complexity is also widely cited by respondents (57%), reflecting mergers, acquisitions, and historical decisions—common across organizations but less often the primary driver.

The study also provides a roadmap for senior executives on how to build flexible, resilient, and sovereign AI systems. To view the full study, visit: https://ibm.biz/ai-sovereignty.

¹ Unpublished data from the IBM Institute for Business Value The Calculus of AI Sovereignty Study (2026).

*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 responsible for AI, data, technology, or related enterprise capabilities 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, and assessing the relationship to resilience, performance and operating economics.

The IBM Institute for Business Value, IBM's thought leadership think tank, combines
global research and performance data with expertise from industry thinkers and leading academics to deliver insights that make business leaders smarter. For more world-class thought leadership, visit: www.ibm.com/ibv. To receive more insights, subscribe to the IdeaWatch newsletter: https://ibm.co/ibv-ideawatch. 

About IBM
IBM is a leading provider of global hybrid cloud and AI, and consulting expertise. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Thousands of government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM's hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM's breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and consulting deliver open and flexible options to our clients. All of this is backed by IBM's long-standing commitment to trust, transparency, responsibility, inclusivity, and service.  Visit www.ibm.com for more information.

Media Contact
Marisa Conway
IBM Corporate Communications
conwaym@us.ibm.com

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SOURCE IBM

FAQ

AI-generated questions and answers. How Rhea-AI works. Not financial advice.

What is the main finding of the June 17, 2026 IBM (IBM) AI sovereignty study?

The study finds many enterprises are highly dependent on AI vendors and lack visibility into AI risks. According to IBM, 71% say switching primary AI vendors is difficult and 91% do not fully understand their AI dependencies.

How many AI-related disruptions did enterprises report in the IBM (IBM) 2026 AI sovereignty research?

Enterprises reported an average of six AI-related disruptions over the past two years. According to IBM, most of these disruptions were linked to vendor services, and 81% of executives say a seven-day vendor outage would cause severe or critical disruption.

What does the IBM (IBM) study say about operating profit protection from AI disruptions?

Organizations with advanced AI control capabilities protect significantly more operating profit from AI disruptions. According to IBM, these leaders protect 55% more operating profit than peers, but only 7% of surveyed organizations currently operate at this advanced control level.

How common are multi-vendor AI environments according to IBM's 2026 study on AI sovereignty?

Multi-vendor AI environments are widely used but often not by deliberate strategy. According to IBM, 73% of organizations describe their AI environments as multi-vendor, mainly driven by independent business unit decisions (69%) and geographic necessity (69%), plus legacy complexity (57%).

What are data residency challenges highlighted in IBM's June 2026 AI sovereignty study (IBM)?

Data residency and sovereignty rules are a major hurdle for global AI deployment. According to IBM, 68% of surveyed executives find it challenging to meet data residency and sovereignty requirements across geographies, complicating how organizations move AI systems and data between environments.

How willing are enterprises to pay more for AI vendor stability in the IBM (IBM) study?

Many enterprises would pay more to secure strategic AI flexibility. According to IBM, 72% of surveyed executives say they would accept a 20% cost increase to maintain AI vendors if it improved strategic flexibility across their AI landscape.