By 2027, more than 40% of AI-related data breaches will result from improper use of generative AI (GenAI) across borders, according to Gartner, Inc. 

The rapid adoption of GenAI has outpaced the development of data governance and security measures, increasing concerns about unintended cross-border data transfers due to the centralized computing power required for these technologies.

Global AI standardization gaps drive operational inefficiency

The lack of consistent global AI standards is forcing enterprises to create region-specific AI strategies, which limits scalability and fragments the market. 

According to Joerg Fritsch, VP analyst at Gartner, organizations are experiencing operational inefficiencies due to localized AI policies, making it harder to manage data flows and maintain quality.

Gartner predicts that as a result, there will be increased investment in AI security, governance, and compliance solutions to enhance transparency and control over AI processes.

AI governance will become a global mandate by 2027

Gartner forecasts that by 2027, AI governance will be a requirement under all sovereign AI laws and regulations. Organizations that fail to integrate the necessary governance models and controls may face a competitive disadvantage, especially if they lack the resources to extend existing data governance frameworks.

To mitigate risks and ensure compliance, Gartner recommends:

• Enhancing data governance: Organizations should monitor cross-border data transfers by expanding governance frameworks to include data lineage and data transfer impact assessments.

• Establishing governance committees: These committees should oversee AI risk management, compliance, and communication regarding AI deployments.

• Strengthening data security: Enterprises should use encryption, anonymization, and Trusted Execution Environments (TEEs) for protecting sensitive data in specific regions.

• Investing in AI TRiSM solutions: Gartner advises businesses to allocate budgets for trust, risk, and security management (TRiSM) products, including AI governance, data security, prompt filtering, and redaction. Gartner predicts that by 2026, enterprises using AI TRiSM controls will reduce inaccurate data consumption by 50%, minimizing faulty decision-making.