The 2026 Test Data Management Report for AI-Ready Enterprises

Executive Summary: Test Data Priorities & Challenges Become Apparent

The 2026 Test Data Management Report for AI-Ready Enterprises offers critical insights into enterprise trends, priorities, and challenges surrounding test data management for the modern, agentic era. This new research reveals the challenges today’s enterprise leaders face in ensuring test data quality, scaling for large datasets, and establishing effective data governance. In this report, our team of experts share how organizations can resolve these challenges and simultaneously ensure AI-ready test data management. 

Key Findings 

• Data quality is a central issue across the report.  
  • It is the #1 test data challenge as well as the main priority in test data automation. (See “The Data Control Paradox: Top Priorities vs. Biggest Barriers” section for more.) 
  • Data quality is also the top barrier to protecting sensitive data in non-production. 
• 27% of respondents also cited scalability as a top priority, while they face challenges related to testing across complex environments (30%).  (Read more under “Test Data Automation Priorities Ranked.“) 
• While organizations fear protecting data will erode data quality: 
  • 57% of respondents report increased sensitive data volume over the past 12 months — a trend that causes complexity for developers, testers, and agents alike. 
• Most organizations use a portfolio approach to deliver protected test data. (See the full list of test data protections in “Solving for Modern Test Data Management Challenges.”) 
  • 86% use static masking. 
  • 60% use dynamic masking. 
  • 51% use synthetic data.

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