Four Ways to Prevent Data Leaks with Shadow AI

[rakhirani458]

Organizations need to carefully design and actively implement various remote application security measures to help IT better control unauthorized and incompletely vetted shadow applications. Remote application solutions, for example, can help organizations that are already in the process of cloud transformation to deploy a Zero Trust Architecture (ZTA). This is achieved by implementing a remote browser isolation solution that evaluates requests based on the company’s access policy and security measures. This will allow IT to begin implementing ZTA at the cloud level for all users, regardless of where they are located or distributed around the world. Another benefit is that there is no need for expensive edge hardware.

One of the biggest concerns for new zealand mobile database 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.