Technology companies could face a 30% increase in legal disputes related to artificial intelligence (AI) regulatory violations by 2028, according to new research from Gartner, Inc.
The findings come from a Gartner survey of 360 IT leaders conducted between May and June 2025, revealing that more than 70% of respondents rank regulatory compliance among their top three challenges when deploying generative AI (GenAI) tools. Yet, only 23% said they are “very confident” in their organization’s ability to manage security and governance during GenAI rollouts.
“Global AI regulations vary widely, reflecting each country’s alignment of AI leadership and innovation with risk mitigation priorities,” said Lydia Clougherty Jones, Senior Director Analyst at Gartner. “This creates inconsistent and often incoherent compliance obligations, complicating alignment of AI investments with enterprise value and exposing businesses to new liabilities.”
Geopolitical Pressures and AI Sovereignty Add Complexity
The study also underscores the growing influence of geopolitics on AI strategy. Among non-U.S. IT leaders, 57% said the geopolitical climate at least moderately affects their GenAI strategy and deployment, with 19% reporting a significant impact. However, nearly 60% of these respondents remain unwilling or unable to adopt non-U.S. GenAI tool alternatives, despite such pressures.
A separate Gartner webinar poll (September 2025) found that 40% of organizations view AI sovereignty — the control nations exert over AI development and governance — as a positive force, while 36% are taking a neutral “wait and see” stance. Moreover, 66% of respondents said they are actively engaged in sovereign AI initiatives, and 52% are already adjusting their strategies or operating models accordingly.
Gartner Recommends Strengthening AI Moderation and Risk Controls
With GenAI productivity tools becoming increasingly embedded in enterprise operations, Gartner urged IT leaders to adopt stronger AI moderation and self-regulation mechanisms, including:
- Training models to self-correct or decline inappropriate prompts (“beyond the scope” responses).
- Instituting rigorous use-case reviews to assess legal, ethical, and safety risks of chatbot outputs.
- Forming cross-functional teams — including data scientists, legal counsel, and decision engineers — to test and document model performance.
- Embedding content moderation safeguards, such as “report abuse” features and AI warning labels.
Gartner’s findings highlight the tension between innovation and accountability as global AI oversight evolves. As regulatory and geopolitical landscapes grow more complex, the firm notes that enterprises must focus on governance, traceability, and transparency to avoid potential legal and reputational fallout.
