Organizations Put Sensitive Data at Risk in AI Model Training
Although 60% of organizations report experiencing data breaches or data theft in software development, AI, and analytics environments – up 11% from last year – most still say sensitive data should be allowed in AI training and testing, according to the 2025 State of Data Compliance and Security Report from Perforce.
Securing sensitive data is crucial for maintaining data compliance, yet the report highlights contradictions that suggest "a lack of shared understanding or consistent guidance within organizations about the safety of using sensitive data in AI model training and initiatives."
For example:
- 91% of respondents say sensitive data should be allowed in AI training and testing.
- 91% are very or extremely concerned about data breaches or theft of sensitive data in non-production environments.
- 82% say it’s safe to use sensitive data in AI model training.
- 84% of organizations allow data compliance exceptions in non-production, despite the threat of compromise.
- 68% worry about privacy and compliance audits.
"Using sensitive data in AI poses tremendous risks,” the report notes, “including regulatory violations, data re-identification, breach and theft, and unpredictable re-sharing of data by models. All of these can cause reputational damage and financial loss."
When asked "What is preventing your organization from protecting all your sensitive data in non-production?" survey respondents cited the following reasons:
- Slows down innovation (61%)
- The quality of data is degraded (54%)
- It’s too big of an effort (20%)
- It’s too difficult to locate all the sensitive data (20%)
"AI models don’t forget inputs, so sensitive customer information should never enter these pipelines in the first place," the report says.
Learn more at Perforce Software.
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