According to recent analysis by Gartner, by 2027, over 40% of data breaches related to artificial intelligence will stem from the misuse of generative AI (GenAI). As GenAI technology rapidly becomes more widespread, businesses and organizations face significant challenges in establishing data governance and security measures. This issue is particularly pronounced in the context of data localization, as these technologies require substantial centralized computing power.
Joerg Fritsch, Vice President and Analyst at Gartner, pointed out that organizations often lack sufficient oversight when integrating GenAI tools, leading to unintended cross-border data transfers. He mentioned, "If employees send sensitive prompts while using GenAI tools, and these tools and APIs are hosted in unknown locations, it poses security risks." While these tools can be used for approved business applications, their potential security risks cannot be overlooked.
Globally, the lack of consistent best practices and data governance standards is another key challenge highlighted by Gartner. This gap leads to market fragmentation, forcing companies to develop strategies for specific regions, thereby impacting their ability to effectively leverage AI products and services worldwide. Fritsch also noted, "The complexity of managing data flows and the quality maintenance issues arising from localized AI policies may lead to operational inefficiencies."
To protect sensitive data and ensure compliance, businesses need to invest in AI governance and security to address these risks. Gartner predicts that by 2027, global AI governance will be widely required, especially under the framework of sovereign AI laws and regulations. Organizations that fail to timely integrate necessary governance models will face competitive disadvantages.
To mitigate risks associated with AI data breaches, Gartner recommends that businesses adopt the following strategies: first, enhance data governance, including compliance with international regulations and monitoring unexpected cross-border data transfers; second, establish governance committees to improve transparency and oversight of AI deployment and data processing; finally, strengthen data security by employing advanced technologies such as encryption and anonymization to protect sensitive information.
Businesses are also encouraged to invest in trust, risk, and security management (TRiSM) products and capabilities related to AI technology. This includes AI governance, data security governance, prompt filtering, redaction, and synthesizing unstructured data. Gartner predicts that by 2026, companies implementing AI TRiSM controls will reduce at least 50% of inaccurate information, thereby lowering the risk of erroneous decision-making.
Key Points:
🔍 Over 40% of AI data breaches will be triggered by the misuse of generative AI.
🛡️ Businesses need to strengthen data governance to ensure compliance and security.
📈 Investing in trust, risk, and security management products related to AI can significantly reduce the generation of erroneous information.
