Seventy percent of surveyed EMEA organisations admit automated artificial intelligence (AI) workflows are interacting with sensitive corporate data without full oversight.
This, as growing executive accountability for regulatory compliance turns AI governance into a boardroom risk.
These findings were released by Veeam Software this week, in new research undertaken by independent polling company Censuswide.
The research was conducted among 1 000 enterprise IT, data and security decision-makers at organisations with more than 500 employees across the UK, Germany, France, and the Middle East and Africa.
The aim of the study is to assess how well EMEA organisations are governing and controlling AI as autonomous AI workflows become embedded in business operations, particularly where those systems access sensitive corporate data.
The findings point to a widening gap between the rapid deployment of autonomous AI and organisations’ ability to understand and control how these systems interact with corporate information.
The research also found that 67% of surveyed organisations have employees creating autonomous AI workflows that IT cannot fully track.
“The AI governance problem is increasingly reaching senior management. Nearly a third of organisations surveyed, or 32%, say rising regulatory pressure and corporate accountability are already creating tension or conflict among executives.”
For C-level leaders, the stakes are also becoming more personal, as 58% of the enterprises surveyed said they now fall under new corporate accountability laws, while 12% said individual responsibilities remain unclear, the report adds.
That uncertainty is being reflected in executive concerns. Forty percent of respondents said they are worried about personal liability or consequences of deploying autonomous AI systems, 39% reported greater board-level scrutiny, and 37% said the increased accountability had contributed to personal stress or anxiety.
“Executives have never had more to think about around data governance and cyber resilience regulations,” says Tim Pfaelzer, GM and senior VP for EMEA at Veeam.
“While the increased stress and tension are completely understandable, if the result is better alignment at the board level, the organisation will be far better positioned to trust its data and AI governance in the agentic era. With greater alignment ultimately comes better data governance, visibility and protection across the organisation.”
Shadow AI outpaces governance
The findings suggest organisations are not simply dealing with employees using unsanctioned generative AI tools. Increasingly, autonomous workflows can operate across business processes and interact with corporate data without IT having a complete picture of what they are doing, the study points out.
This creates a governance problem that is difficult to address through conventional controls, particularly as businesses increase their use of AI agents and automated processes.
“EMEA organisations are still getting to grips with governance in the new agentic era,” adds Pfaelzer. “But the data shows the industry is having the wrong conversation about AI trust. Trying to control thousands of autonomous agents one-by-one simply doesn’t scale. To make AI safe at the enterprise level, organisations need to secure, govern and understand the data those agents depend on.”
Organisations are responding partly by changing where and how AI models are deployed.
The research found that 41% of EMEA organisations are building their own local or sovereign AI models specifically to address shadow AI concerns. A further 49% are adopting hybrid approaches, combining local or sovereign models for sensitive workloads with global models for more general applications.
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