As AI adoption accelerates, having AI-ready data is no longer nice to have, it’s essential. But AI data readiness continues to be a significant barrier to success – and it becomes even more of a challenge when we’re talking about unstructured data. In fact, Gartner has predicted that 30% of AI projects will fail by the end of this year due to unresolved data quality & readiness issues.
Is your data ready for AI? Whether you’re preparing for agentic AI, generative AI, copilots, or other data-driven initiatives, use our checklist to ensure your data is relevant, organized, cleansed, secured, and ready for what’s next.
Checklist for AI-Ready Data
📄 Downloadable AI-Ready Data Checklist
Is Your Content Platform Built to Support AI-Ready Data?
- Assess your storage systems for AI readiness: Can your current platform integrate with modern AI and analytics technologies, or is your data stuck in legacy systems?
- Migrate unstructured data from legacy storage systems to modern, AI-capable platforms.
- Set up continuous synchronization to ensure your data stays current and accessible.
➡️See how HW Kaufman Group successfully modernized their content platform, achieving seven-figure cost savings and direct revenue impact. Read the case study.
Is Your Data High-Quality and Relevant for AI Initiatives?
- Define your AI goals: conduct a values assessment and target high-impact GenAI use cases.
- Implement an intelligent, AI-ready data management platform that can curate focused, use-case-specific data sets that feed your AI models with the right data.
- Automatically eliminate outdated, duplicate, or irrelevant files to eliminate hallucinations and boost AI accuracy.
- Regularly audit your content to keep data clean, usable, and AI-ready for future initiatives.
Is Your Enterprise Content Properly Organized for AI Efficiency?
- Strengthen data governance to ensure AI-ready data is easy to find, protect, and manage across your organization.
- Automate the classification of unstructured data based on its contents, and apply rich, business-relevant metadata at scale.
- Organize files into correct taxonomies and move them to appropriate locations to fuel your data initiatives (or prevent them from being used for training).
- Customize entity recognition and document classification to match your business needs as they evolve.
Has Sensitive Data been Cleansed from Datasets for Responsible AI?
- Prevent sensitive data like PII, intellectual property, or other non-public information from being used in AI training by enforcing classification-based controls.
- Apply redaction, encryption, and anonymization to protect sensitive information without compromising the high-value insights for AI and other data-driven initiatives.
- Automate compliance processes to safeguard sensitive data as AI use grows.
Are Your Security Measures Robust Enough for AI-Driven Operations?
- Enforce strict access controls and continuously audit sharing permissions to ensure only authorized users have access to sensitive data.
- Apply security labels and policies—like Microsoft Purview Information Protection (MPIP) or Box Shield—in real time to safeguard content automatically.
- Quarantine exposed or high-risk files immediately and block unauthorized sharing to prevent data breaches.
- Regularly review and update enterprise-wide security policies to stay ahead of evolving threats and maintain trust in your AI-ready data.
The Smarter Way to Make Your Content AI-Ready
Getting your unstructured data AI-ready is critical to unlocking the full potential of your AI and data-driven initiatives. Remember, content readiness is not a destination; it’s a journey. This checklist helps you identify key gaps, but every organization’s data landscape and journey is unique. Ready to take the next step? Connect with one of our unstructured data experts to begin assessing your data readiness for AI and build a roadmap for success.
Whether your goal is to reduce risk, support AI adoption, improve compliance, or drive efficiency, DryvIQ ensures your unstructured data is always ready for what’s next.
