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Risk Management

IBM report cover examining AI sovereignty, vendor lock-in, and governance risks for enterprise AI systems.

IBM Finds AI Sovereignty Gap Raising Governance Risks

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Only 9% of executives say they have an excellent understanding of their AI dependencies as organizations face growing vendor lock-in and operational resilience challenges.

 

Key Takeaways

  •         Only 9% of executives say they have an excellent understanding of their AI dependencies.
  •         71% say switching their primary AI vendor or model would be difficult today.
  •         72% would accept a 20% cost increase to maintain multiple AI vendors for strategic flexibility.
  •         81% say a seven-day outage at a primary AI vendor would have a severe or critical impact on operations.
  •         Organizations with stronger control across data, models, and infrastructure protect 55% more operating profit from AI-driven disruption.

 

The IBM Institute for Business Value released a new report examining how organizations are managing AI sovereignty as AI becomes increasingly embedded in business operations.

Based on a survey of 1,000 senior executives, the report found that many organizations are expanding AI adoption while struggling to maintain visibility into the vendors, models, infrastructure, and data dependencies that support those systems.

The findings suggest AI sovereignty is emerging as a governance issue as organizations seek greater control over the technologies driving operational decisions.

Organizations lack visibility into AI dependencies

Only 9% of executives said they have an excellent understanding of their dependencies on AI vendors, models, and infrastructure.

At the same time, 71% said switching their primary AI vendor or model would be difficult if required today. IBM said the findings highlight the growing challenge of maintaining flexibility as organizations become increasingly reliant on AI services and providers.

The report defines AI sovereignty as an organization’s ability to move data, swap models, and shift workloads across environments when technical, commercial, or regulatory conditions change.

These dependencies have become more complex over the past two years, with executives reporting unexpected price increases, usage restrictions, service deprecations, changes to data-handling practices, and geographic access limitations.

Vendor concentration creates resilience concerns

The study found that 81% of executives believe a seven-day outage affecting a primary AI vendor would have a severe impact on business operations.

In addition, 75% of executives who switched or attempted to switch AI vendors over the past two years said the process was difficult due to data portability issues, model revalidation requirements, compliance obligations, and being tied to a specific vendor’s technology.

Despite those challenges, many organizations are willing to invest in flexibility. The report found that 72% of executives would pay 20% more to maintain multiple AI vendors if doing so improved strategic freedom and reduced dependence on a single provider.

IBM noted that 28% of organizations already use four or more AI vendors as part of a strategy to maximize flexibility and avoid lock-in.

Governance and control linked to business outcomes

The report found that organizations with the strongest control across data, models, infrastructure, and applications protect 55% more operating profit from AI-driven disruption than organizations with less control.

The report also found that 57% of executives said replacing a core AI model would require significant decoupling or even a complete system rebuild. In comparison, 56% said moving core AI systems and applications to a different vendor would take at least six months.

As AI systems become more deeply embedded in business operations, IBM said organizations are increasingly evaluating how much control they maintain over the data, models, and infrastructure that support those capabilities.

Abstract AI network image for coverage of an MIT survey on catastrophic AI risks.

MIT Survey Finds 18 AI Risks That Could Cause Catastrophic Harm Within Five Years

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Even after practical safeguards are in place, experts still say that five AI risk categories have a 10% probability of causing catastrophic harm.

 

Key Takeaways

  • 18 of 24 AI risk categories have more than a 10% probability of catastrophic harm by 2030 under a business-as-usual scenario.
  • Even with pragmatic mitigations in place, experts still rated five AI risks above the 10% probability threshold.
  • Information, finance, and national security were identified as the sectors most vulnerable to AI-related risks.
  • The highest-rated risk categories included dangerous AI capabilities, competitive dynamics, weapons and cyberattacks, power centralization, and false information.
  • Weapons and cyberattacks were the most frequently cited expert concern, selected by 26.8% of respondents.

A new report from MIT, Prioritizing the Risks from Artificial Intelligence, asked 272 AI experts to assess which AI risks are most severe, who is most vulnerable to them, and who should be responsible for addressing them. The study used a structured survey method in which experts answered questions over three rounds and reviewed anonymous feedback between rounds to build expert consensus across 24 categories of AI risk. The results suggest experts see meaningful catastrophic risk across much of the AI landscape over the next five years.

 

Catastrophic risk assessments

Experts identified 18 of 24 AI risk domains as having a greater than 10% probability of catastrophic harm in the next five years under a business-as-usual scenario. The report defined catastrophic harm as more than one million deaths, more than $100 billion in financial losses, or comparable societal-scale harm.

The five risk categories viewed as most severe were:

  • Dangerous AI capabilities: AI systems enabling large-scale harm or loss of control.
  • Competitive dynamics: Pressure to deploy AI quickly at the expense of safety.
  • Weapons and cyberattacks: AI enabling stronger cyber operations or weapons.
  • Power centralization: AI concentrating power among a few organizations or governments.
  • False information: AI-generated misinformation that undermines trust.

Researchers also evaluated a scenario where governments and companies implemented practical, cost-effective safeguards. While risk levels declined across all 24 categories, five remained above the 10% catastrophic-harm threshold: dangerous AI capabilities, weapons and cyberattacks, power centralization, environmental harm, and inequality and unemployment. Even after those safeguards were implemented, all 24 risks still had at least a 5% probability of causing catastrophic harm.

 

Most vulnerable sectors

The report asked experts to assess the vulnerability of 14 industry sectors to AI-related risks.

Information and national security were rated the most vulnerable sectors. Experts said those sectors face heightened exposure because AI is increasingly embedded in decision-making, information distribution, and critical systems. Finance and insurance also ranked near the top due to risks related to fraud, scams, AI security weaknesses, and system failures.

Healthcare received high vulnerability ratings for privacy loss, discrimination, and unsafe reliance on AI systems. By contrast, the accommodation and food services sector (including hotels, lodging, and restaurants), agriculture, manufacturing, and arts and entertainment were viewed as less vulnerable. However, experts noted they could still face broader economic and workforce effects.

 

Top concerns

When experts were asked to identify the three AI risks that concerned them most, weapons and cyberattacks ranked first at 26.8%, followed by power centralization at 23.5%, disinformation and influence at 22.1%, the erosion of a shared understanding of reality at 21.6%, and dangerous capabilities at 21.6%.

The report assigns much of the responsibility for addressing these risks to AI developers, governments, regulators, and standards bodies. Its release comes as policymakers in the United States, Europe, and elsewhere continue debating how AI systems should be governed, tested, and monitored as adoption accelerates.

Abstract blue geometric visualization of AI risk surging as the top long-term business threat, AI Risk 2026 Emerging Risk Survey

Actuaries Rank AI as the Top Long-Term Business Risk

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In the Society of Actuaries’ 19th annual survey, 100+ insurance executives ranked AI 4th for 2026 and 1st for the three-year outlook.

Key Takeaways

  • 27% of C-suite executives named AI as their top long-term risk. Near-term, 8% named it.
  • Financial volatility (25%) and geoeconomic and globalization shifts (19%) led the 2026 rankings.
  • 53% of consulting firm executives named AI as their top long-term risk.
  • AI + other risks was the top risk combination, named by 33% of executives.
  • Geopolitical risks had the lowest carryover: 24% of executives who named one near-term also named one long-term.

The Society of Actuaries Research Institute (SOA) and Casualty Actuarial Society (CAS) published the 19th Annual Emerging Risk Survey, drawing on responses from 100+ Chief Risk Officers, Chief Actuaries, and senior consulting partners in insurance and financial services. Participants ranked the risks most likely to affect their organizations in 2026 and over the next 3 or more years.

 

AI is the top long-term risk

27% of executives named AI adverse outcomes as the top risk over the next 3 or more years. Financial volatility ranked second at 17%. Geopolitical risks fell out of the top five entirely.

Consulting firms are the most concerned. 53% of consulting firm executives named AI as their top long-term risk. Even in the near term, 35% named it. That is the highest near-term share for AI of any responder group.

Property and casualty insurance executives also named AI as their biggest long-term concern at 18%, tied with extreme weather events.

 

Near-term concerns

For 2026, financial volatility leads. 25% of executives named it as the top near-term risk. 19% named geoeconomic and globalization shifts, driven by tariffs, export controls, and sanctions. AI ranked fourth at 8%.

Geopolitical risks had the lowest carryover of any category. Only 24% of executives who named a geopolitical risk near-term also named one long-term.

 

When risks are combined, those mixed with AI create the most concern

33% of respondents said AI combined with other risks is a top concern. 

Among these combinations, AI paired with cyber threats and AI paired with financial volatility topped the list at 9% each. 

The survey is in its 19th consecutive year. Disruptive technology, the broader category that includes AI, has ranked in the top three emerging risks since 2023, spiking in 2026.