Some SaaS threats are visible, while others are hidden, posing risks to organizations. Wing’s research shows that 99.7% of organizations use AI functionalities in applications. These AI tools provide seamless experiences, but they also pose risks of compromising sensitive business data and IP.
Wing found that 70% of the top 10 AI applications may use data for training, involving retraining, human review, and sharing with third parties. These risks are often buried in fine print, leaving security teams struggling. This article explores risks, examples, and best practices for SaaS security.
Four Risks of AI Training on Your Data
AI training on your data poses risks to privacy, security, and compliance:
1. Intellectual Property (IP) and Data Leakage
Training AI with your data can expose IP and sensitive data, risking business strategies and confidential information.
2. Data Utilization and Misalignment of Interests
AI improving capabilities with your data can lead to misalignments, potentially benefiting competitors.
3. Third-Party Sharing
Data shared with third parties for AI training raises data security concerns.
4. Compliance Concerns
Non-compliance with regulations on data usage can result in fines and legal actions.
What Data Are They Actually Training?
Understanding the data used for AI training in SaaS applications is crucial for assessing risks and implementing data protection measures.
Navigating Data Opt-Out Challenges in AI-Powered Platforms
Opting out of data usage in SaaS applications can be challenging due to scattered options. A centralized SSPM solution can help streamline opt-out processes.
By prioritizing visibility and compliance, organizations can protect their data from AI training risks. Leveraging tools like Wing’s SSPM solution can empower users to navigate AI data challenges securely.
