This Komprise 2026 State of Unstructured Data Management report summarizes the responses of 300 global enterprise storage IT directors, VPs and C-level executives at companies with more than 1,000 employees in the United States and shares insights and strategies for unstructured data analysis, management and movement.
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Report Highlights
Unstructured Data Management Challenges & Priorities
- The top data storage priorities: cost optimization (64%), data preparation / classification for AI (61%) and cloud migration (54%)
- Top technical challenges for unstructured data management:
- Classifying data for AI (58%)
- Moving data without disruption (53%)
- The top business challenge for unstructured data management: reducing data risk from AI (62%)
- The greatest data concern for GenAI is security: corporate data leakage (46%)
- 47% worry about departments lacking visibility into storage spend and data use
- The top challenges in prepping data for AI:
- Classifying and tagging (56%)
- Data governance and security concerns (46%)
- Top future requirements for unstructured data management:
- Data classification and tagging (61%)
- Analytics and reporting (60%)
- Sensitive data detection (57%)
- The top skills gaps:
- AI data management 62%
- Cloud storage strategies (60%)
- Data security/compliance (49%)
Unstructured Data Management Strategies for 2026
- 40% will increase their IT budget to pay for AI
- To meet security and AI requirements:
- 64% upgrading data storage and data management platforms
- 58% are creating an internal task force of IT, security, legal and others to develop an AI strategy
- 53% will be adding staff, with a focus on hiring IT infrastructure leaders focused on developing the AI foundation
- 49% hiring engineers and developers with AI expertise
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