Gartner Predicts 30% Surge in Tech Firms' Legal Disputes Due to AI Regulatory Violations by 2028

AI Regulatory Challenges on the Horizon

A recent Gartner survey of 360 IT leaders involved in the rollout of generative AI (GenAI) tools has revealed a looming crisis in the tech industry. By 2028, artificial intelligence (AI) regulatory violations are projected to cause a 30% increase in legal disputes for tech companies 1

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Compliance and Security Concerns

The survey highlighted significant challenges in regulatory compliance and security management:

• Over 70% of IT leaders identified regulatory compliance as one of the top three challenges for widespread GenAI deployment 1

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• Only 23% of respondents expressed high confidence in their organization's ability to manage security and governance components when implementing GenAI tools 1

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Lydia Clougherty Jones, Senior Director Analyst at Gartner, explained, "Global AI regulations vary widely, reflecting each country's assessment of its appropriate alignment of AI leadership, innovation and agility with risk mitigation priorities" 1

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Geopolitical Impact on GenAI Strategy

The survey also revealed the growing influence of geopolitical factors on GenAI deployment:

• 57% of non-US IT leaders reported that the geopolitical climate moderately or significantly impacted their GenAI strategy and deployment 1

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• Despite this, nearly 60% of these respondents were unable or unwilling to adopt non-US GenAI tool alternatives 1

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AI Sovereignty and Organizational Response

A separate Gartner webinar poll of 489 respondents provided insights into organizational attitudes towards AI sovereignty:

• 40% of organizations viewed AI sovereignty positively, seeing it as an opportunity 1

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• 36% adopted a neutral, "wait and see" approach 1

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• 66% of respondents were proactively engaged in responding to sovereign AI strategies 1

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• 52% reported making strategic or operational changes in response to sovereign AI 1

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Recommendations for IT Leaders

To address these challenges, Gartner recommends that IT leaders:

1. Strengthen output moderation by training models for self-correction.
2. Implement rigorous use-case review procedures to evaluate risks.
3. Enhance model testing and sandboxing with cross-disciplinary teams.
4. Design pre-testing protocols and validate model outputs against unwanted conversational output 1

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