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The 2026 Test Data Management Report for AI-Ready Enterprises
- Letter from the Authors
- Ranking Test Data Priorities: Why Data Quality Claims the #1 Spot
- The Data Control Paradox: Top Priorities vs. Biggest Barriers
- The Problem with Process: Test Data Bottlenecks Are Stalling Workflows
- Solving for Modern Test Data Management Challenges
- Key Takeaways: How You Can Make the Next Step Toward AI-Ready Test Data Management
- Respondents Snapshot: Segments, Industries, & Job Titles
- Key Terms to Know
Report > The 2026 Test Data Management Report for AI-Ready Enterprises
Solving for Modern Test Data Management Challenges
Quality, flexibility, scalability, and speed are all among top challenges and barriers to test data automation. We asked enterprises what they are using to protect their test data, and we found most are taking a portfolio approach, leveraging multiple solutions at once. They are using static (86%) and dynamic data masking (60%), synthetic data (51%), tokenization (33%), and data subsetting (29%) — picking the ones they need and having them work together for a well-rounded strategy.
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