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ABBYY Study Finds UK Business Leaders Disagree on Who Has Ultimate Responsibility When AI Goes Wrong

- 2026 ABBYY Who Answers for AI: The Governance Gap reveals that governance is struggling to keep pace with innovation
- AI ROI is falling short of expectations and data quality is the top reason
- 70% say data governance requirements slow AI deployment
New research commissioned by ABBYY reveals that AI is delivering value, but business leaders are divided over who should ultimately be responsible when AI systems produce harmful or incorrect outputs.
ABBYY’s new report, Who Answers for AI: The Governance Gap, surveyed 200 senior managers in businesses of 100+ employees located in the UK, conducted by Opinium. It found that over a third (35%) of business leaders at businesses using AI believe responsibility should be shared between the organisation and the vendor when an AI system produces harmful or incorrect outputs. Meanwhile over a quarter (27%) believe the organisation using the AI should bear primary responsibility, and a fifth (19%) believe it lies fully with the AI vendor. A further 9% believe the end user should be responsible, and 10% believe regulators should take the lead.
Lack of clarity around AI governance and responsibility reflects wider AI concerns
Just over a quarter (26%) of business leaders using AI in their organisation say they completely trust AI systems to produce accurate outputs, 29% completely trust AI to explain how important decisions were reached, and 28% completely trust it to protect confidential information. Confidence falls further when it comes to risk, with just 22% saying they completely trust AI systems to operate without introducing unacceptable risks.
In addition, more than half (57%) of business leaders say AI is being adopted faster than their organisation can effectively govern it, highlighting concerns that governance is struggling to keep pace with the speed of innovation.
These concerns are having a tangible impact on the pace of AI adoption. Nearly a third (31%) say ethical concerns in their organisation considerably slow down deployment of AI initiatives, highlighting the challenge businesses face in balancing innovation with responsible adoption.
Data governance needed to scale AI adoption
Data governance — the controls that ensure data is accurate, secure and compliant — is a major barrier to scaling AI, with 70% of business leaders using AI in their organisation saying data governance requirements slow AI deployment in their organisations.
This slowing could be impacting ROI, with less than half (48%) of business leaders at organisations using AI saying their AI initiatives have exceeded their expected targets, and 9% saying AI performance is below expectations. This raises questions about whether businesses are putting the right structures in place to realise the full value of AI.
Challenges impacting AI ROI
Concerns around data quality are a key barrier to achieving greater ROI from AI, with 17% of business leaders citing it as their top challenge. Integration with existing systems (20%) and regulatory uncertainty were other top concerns (15%).
Part of the challenge may be a lack of shared understanding within organisations. Knowledge of who is responsible for AI decreases the more junior employees are. Business leaders at organisations using AI say 86% of senior leadership knows who is responsible for developing, implementing, and managing AI across their organisations, 81% say middle management knows, and 72% say the same for junior employees.
Roman Kilun, Chief Compliance Officer at ABBYY
AI governance emerges as a critical factor in successful adoption
Yet the findings suggest that effective governance can play a key role in helping organisations realise greater value from AI. More than three quarters (76%) of business leaders at organisations using AI say governance has made AI initiatives at their organisation more successful, while 77% say their organisation’s governance approach effectively balances risk mitigation with the need to deliver AI quickly.
The majority of business leaders (81%) whose organisations currently use AI say their organisation has a formal AI governance framework in place. However, governance maturity varies, and only half (53%) have an AI incident reporting process, 44% have an AI incident response plan, 29% have an AI kill switch, and 38% have AI rollback capabilities. Just 5% say their organisation has no AI incident management capabilities.
More organisations are also planning to strengthen their governance approach, with 17% of business leaders at organisations using AI saying their organisation does not currently have official AI governance in place but plans to develop one within the next 12 months.
Human oversight important to AI governance
Those with AI governance frameworks in place are already seeing practical benefits. More than half say governance makes it easier to develop AI systems (64%), scale AI initiatives beyond the pilot stage (63%), and encourage employee adoption of AI systems (62%).
Human oversight remains important, with 53% of business leaders saying humans review all important AI decisions before action is taken.
Organisations we work with are moving beyond pilots and proofs of concept into execution, and clear frameworks and a shared understanding of responsibility are critical to building confidence in AI. At ABBYY, we’re committed to being transparent about our own governance approach and supporting customers on that journey.
Roman Kilun, Chief Compliance Officer at ABBYY






