AI violations to cause 30% spike in legal disputes for tech cos by 2028: Gartner

Only 23% of IT leaders confident in organization’s ability to manage security and governance when rolling out GenAI tools, a Gartner survey has revealed

by e4m Staff
Published: Oct 7, 2025 3:35 PM | 2 min read

AI regulatory violations will result in a 30% increase in legal disputes for tech companies by 2028, according to Gartner, Inc., a business and technology insights company.

The Gartner survey of 360 IT leaders involved in the rollout of generative AI (GenAI) tools found that over 70% indicated that regulatory compliance is within their top three challenges for their organization’s widespread GenAI productivity assistants deployment.

Only 23% of respondents are very confident in their organization’s ability to manage security and governance components when rolling out GenAI tools in their enterprise applications.

“Global AI regulations vary widely, reflecting each country’s assessment of its appropriate alignment of AI leadership, innovation and agility with risk mitigation priorities,” said Lydia Clougherty Jones, Sr. Director Analyst at Gartner. “This leads to inconsistent and often incoherent compliance obligations, complicating alignment of AI investment with demonstrable and repeatable enterprise value and possibly opening enterprises up to other liabilities.”

In a Gartner September 3, 2025, webinar poll, 40% of the 489 respondents indicated that their organization's sentiment to AI sovereignty - defined as the ability of nation-states to control the development, deployment, and governance of AI technologies within their jurisdictions - is “positive” (as in viewed with hope and opportunity), and 36% indicated their organization’s sentiment was “neutral” (as in taking a “wait and see” approach).

In the same poll, 66% of the respondents indicated they were proactive and/or engaged in response to sovereign AI strategy, and 52% indicated that their organization was making strategic or operating model changes as a direct result of sovereign AI.

Engineer self-correction by training models to self-correct and not answer certain questions in real time, communicating instead a phrase such as “beyond the scope.”

Create rigorous use-case review procedures that evaluate the risk of “chatbot output to undesired human action,” from legal, ethical, safety and user impact perspectives; use control testing around AI-generated speech, measuring performance against the organization’s established risk tolerance.