IBM: 80% of EMEA firms report AI incidents to board, but only 40% update governance policies

AI Incidents Reach Board Level Across EMEA Organizations

A comprehensive IBM survey of 3,221 senior executives across Europe and the Middle East has revealed that 80% of organizations reported AI-related incidents to their board or C-suite over the past year1

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. These AI-related incidents included agent failures, data exposures, AI-driven decision errors, and AI security breaches3

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. The research, conducted by Censuswide between September 14 and 24, 2026, surveyed business leaders at organizations with 1,000 or more employees across eight countries including the UK, France, Germany, Italy, Spain, the Netherlands, Saudi Arabia, and the UAE3

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Critical Gap in AI Governance Policies Despite Board Escalations

Despite the high rate of board level escalations, only 40% of organizations updated their AI governance policies or frameworks in response to these incidents2

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. This represents a significant governance gap as companies struggle to balance AI excitement with realism. Ana Paula Assis, IBM Senior Vice President and Chair for EMEA and APAC, emphasized at the Think EMEA event in London that organizations face a fundamental challenge: "How do you balance the speed of innovation with the implementation of governance?"1

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. IBM itself has demonstrated the business value of structured AI deployment, reporting $5.5 billion in savings through improved productivity and efficiency1

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Agentic AI Deployment Outpaces Governance Readiness

The survey revealed that 35% of respondents are already running agentic AI in production, while 75% expect AI agents to have some level of decision-making autonomy by 20273

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. However, only 37% believe their current governance systems are designed to scale with agentic AI deployment2

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. When AI deployment moves faster than governance frameworks, 56% of organizations continue within agreed risk limits while governance adapts, while 33% delay deployment until governance is ready3

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. This tension highlights the challenge of maintaining accountability and trust in AI while pursuing innovation.

Divided Views on AI Risk Responsibility and Liability Frameworks

Nearly all executives surveyed (98%) have formally assigned responsibility for AI governance at board level, including 26% with a dedicated board-level AI committee3

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. The CIO or CTO was most frequently cited as having assigned responsibility for adverse outcomes from AI agents, selected by 17% of respondents3

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. Yet views on legal liability remain split, with organizations prioritizing different approaches: 33% focus on formal legal frameworks defining AI vendor liability for agent failures, 32% emphasize defined human escalation thresholds, 30% prioritize real-time monitoring and audit trails of agent decisions, and 29% stress the ability to immediately halt agent activity2

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Third-Party AI Risk and Financial Quantification Gaps

The research uncovered significant blind spots in AI governance frameworks. Only 37% of respondents have a formal, board-reviewed quantification of the financial risks created by gaps in their AI governance3

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. Additionally, 54% acknowledge gaps in how their governance framework covers AI systems used by vendors, technology partners, and supply chain participants, with only 21% continuously monitoring third-party AI risk3

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. Assis noted that without adequate security, accountability, and responsibility measures, scaling AI in corporate environments becomes extremely difficult, particularly in highly regulated industries1

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AI as a Business Model Demands Governance as Value Enabler

Assis emphasized a fundamental shift in how organizations must view AI: "AI is no longer just supporting the business. It has become the business model. The organizations pulling ahead are not just adding AI, but rethinking how systems, decisions and processes work together with AI"1

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. She stressed that AI governance has moved beyond being a compliance exercise to becoming a business requirement and value enabler2

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. Organizations that can scale AI with accountability and trust will realize the greatest business value, requiring governance built into how agents operate with clear boundaries on capabilities, clear ownership when issues arise, and controls that work in real-time2

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