Enterprise organizations remain confident in their ability to protect sensitive data, but many continue to experience security breaches, compliance failures and growing risks tied to artificial intelligence, according to Perforce Software‘s latest State of Data Compliance and Security Report.
The report, based on a survey of more than 500 enterprise leaders conducted with Hanover Research, found that 98% of respondents are confident in their organization’s data protection capabilities. Despite that confidence, 34% reported experiencing data breaches or theft, while 43% said their organizations had failed compliance audits.
The findings highlight what Perforce describes as a growing disconnect between enterprise confidence and operational reality as organizations expand AI initiatives and manage increasingly complex data environments.
Enterprises Continue to Face Data Protection Challenges
While nearly every organization surveyed has data masking policies in place, enforcement remains inconsistent.
According to the report, 99% of respondents said their organizations require data masking, yet 84% also allow compliance exceptions that can increase exposure to sensitive information.
Enterprise leaders also expressed ongoing concerns about protecting non-production environments, with 77% worried about data breaches or theft and 74% citing audit failures as a significant risk.
“We’re seeing a contradiction in the data: strong confidence despite concerns and real-world risks,” said Ross Millenacker, senior product manager for Perforce Delphix and one of the report’s authors. “That tension highlights how challenging it is to protect sensitive data at scale without the right solutions, particularly as organizations expand into agentic development.”
AI Is Creating New Data Security Priorities
The survey also found that organizations are increasing investments in protecting AI data.
While 98% of respondents expressed confidence in safeguarding sensitive data used in AI workflows, 68% remain concerned about data leaks and 62% worry about training data breaches involving AI models.
Perforce reported that 80% of organizations plan to increase investments in AI data protection technologies during 2026 and 2027, particularly for machine learning model training and fine-tuning.
The report also identified data quality as the leading challenge for securing AI systems, with more than half of respondents identifying it as their biggest obstacle.
Databricks and Snowflake Emerge as Security Priorities
As enterprise AI adoption expands, organizations are placing greater emphasis on securing modern analytics platforms.
The survey found that Databricks and Snowflake have become among the highest-priority platforms requiring data masking, reflecting their growing role in AI development, analytics and enterprise data processing.
Perforce said the trend underscores the increasing importance of protecting the data that powers AI applications rather than focusing solely on the AI models themselves.
Growing Focus on Enterprise Data Governance
The State of Data Compliance and Security Report is part of Perforce’s broader research examining how enterprises manage data governance, privacy and compliance as AI adoption accelerates.
The company said future reports will explore additional topics, including AI data privacy, synthetic data and test data management as organizations continue modernizing software development and AI workflows.
The Bottom Line
As enterprises invest heavily in AI, protecting the data that powers those systems is becoming just as important as securing the models themselves. Perforce’s findings suggest many organizations remain confident in their security strategies despite continuing breaches, audit failures and compliance gaps. The report highlights the growing need for stronger data governance, consistent policy enforcement and AI-specific security controls as enterprise AI adoption accelerates.