Four Ways to Prevent Data Leaks with Shadow AI

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One of the biggest concerns for organizations in the GenAI world is data security. When feeding confidential company information, source code, or financial data into AI tools, there are concerns about the exposure of sensitive data and whether that information will be used to train underlying models. Some industries, such as healthcare or financial services, are particularly sensitive to data breaches.
To prevent such risks, you need to follow four rules:

Strengthen all key security measures governing data flows.
Add AI-specific security enhancements.
Improve solutions for remote workers to mitigate risks associated with shadow AI.
Accept that employees strive for productivity, and AI can be useful if properly managed.
These methods will ensure a secure data environment.

Gartner: Top Generative AI Cybersecurity philippines mobile database for 2024
21.03.2024
To help all stakeholders understand key trends in generative artificial intelligence (GenAI) cybersecurity and make informed decisions to mitigate risks, Gartner presented its predictions and recommendations at the Gartner Security & Risk Management Summit in Sydney, EnterpriseAI reports.

With 2024 set to be another big year for GenAI, it's no surprise that many of Gartner's predictions are related to the technology.

Organizations, governments, academics, and more are looking for ways to harness the transformative capabilities of GenAI. According to Salesforce’s 2023 Generative AI in IT Survey, the majority of IT leaders (67%) consider GenAI a priority for their business in the next 18 months. While there’s a lot of excitement about the prospects of GenAI, there are also some concerns, including uncertainty about how GenAI will impact cybersecurity on multiple fronts.