Unstructured data governance
Unstructured data governance applies the same rigor you use for databases — access controls, retention policies, quality standards, classification — to documents, emails, recordings, and other content that lives outside your structured systems. Most organizations govern their databases carefully but let their shared drives, email archives, and document repositories grow unchecked. As AI starts reading and acting on this content, governing it becomes urgent — because an AI agent with access to unclassified documents doesn't know which ones are drafts, which are outdated, and which contain sensitive information.
Go deeper
Your AI assistant just surfaced a three-year-old draft proposal to a current client — one with pricing 40% below your current rates and promises you never intended to keep. The client saw it in a system-generated summary because nobody ever deleted the draft from the shared drive, and nobody told the AI which documents are current and which are abandoned. Your shared drive has 50,000 files. Maybe 20,000 are current. The AI treats all 50,000 as equally valid because nobody has classified them.
The trap most companies fall into is governing their databases meticulously while letting their document repositories become digital landfills. When humans were the only readers, it was annoying but manageable — people learned which folders to ignore. AI doesn't have that instinct. It reads everything with equal weight. Unclassified, ungoverned documents become liabilities the moment you give an AI system access to them.
Questions to ask
- How many files are in our shared drives, and what percentage have been reviewed, classified, or confirmed as current in the last two years?
- Before giving an AI tool access to our documents, do we have a process to define which content is authoritative versus draft, archived, or deprecated?
- Who owns the governance of our unstructured content — and do they know they own it?