Global GenAI Adoption to Fuel AI Data Breach Risks, Gartner Predicts

By 2027, more than 40% of AI-related data breaches will be caused by the improper use of generative AI (GenAI) across borders, according to Gartner, Inc. As GenAI technologies are rapidly adopted by end-users, the development of data governance and security measures has struggled to keep pace, raising concerns over data localization. The centralized computing power required to support these technologies is fueling these concerns.

Joerg Fritsch, VP Analyst at Gartner, explained that unintended cross-border data transfers often occur due to inadequate oversight, particularly when GenAI is integrated into existing products without clear descriptions or announcements. Organizations are increasingly noticing changes in content generated by employees using GenAI tools. While these tools are suitable for approved business applications, they can pose security risks if sensitive prompts are sent to AI tools or APIs hosted in unknown locations.

The lack of consistent global best practices and standards for AI and data governance is exacerbating challenges. This fragmentation forces enterprises to adopt region-specific strategies, limiting their ability to scale operations globally. The complexity of managing data flows and ensuring quality due to localized AI policies can lead to inefficiencies. Organizations must invest in AI governance and security to protect sensitive data and comply with international regulations. This growing need is expected to drive market growth for AI security, governance, and compliance services, as well as technology solutions that improve transparency and control over AI processes.

Gartner predicts that by 2027, AI governance will become a requirement of all sovereign AI laws and regulations worldwide. Organizations that cannot integrate the necessary governance models and controls will face competitive disadvantages, especially those lacking the resources to extend existing data governance frameworks quickly.

To mitigate the risks of AI data breaches, especially from cross-border misuse of GenAI, Gartner recommends several strategies for enterprises. First, they should enhance data governance by extending frameworks to include AI-processed data and monitoring unintended cross-border data transfers. Data lineage tracking and privacy impact assessments should be part of these frameworks. Organizations are also encouraged to establish AI governance committees responsible for overseeing AI deployments, ensuring risk and compliance management, and providing transparent communication about data handling.

Additionally, companies should strengthen data security by utilizing encryption, anonymization, and Trusted Execution Environments to protect sensitive data. This includes applying advanced anonymization technologies, such as Differential Privacy, when data must be transferred across regions. Gartner also advises investing in AI Trust, Risk, and Security Management (TRiSM) products. These products focus on AI governance, data security, and prompt filtering, with Gartner forecasting that by 2026, enterprises applying AI TRiSM controls will consume at least 50% less inaccurate or illegitimate information, thus reducing faulty decision-making.

With AI governance set to become a global mandate, organizations must take action now to ensure compliance, protect sensitive data, and maintain their competitive edge in an increasingly AI-driven world.