Shadow AI is the use of AI tools (ChatGPT, Claude, Gemini, Copilot, built-in assistants…) outside the official company framework : no DPIA, no document control, no traceability. It's not marginal - it's the daily reflex of teams under deadline pressure.
Why bans fail
IT and DPO teams publish policies: "no personal data in public AI tools." In practice:
- Tools are already installed on workstations (browser, extensions, mobile)
- Productivity gains are immediate and visible
- Sanctions are rare; business need is real
Result: usage continues, but invisibly - worse for risk than controlled use. You can't audit what you can't see.
From prohibition to securing
A pragmatic strategy channels rather than pretending to shut AI down:
- Train on data forbidden in plain text (health, raw HR, unmasked secrets)
- Provide pseudonymisation before sending - fast, without changing the preferred AI tool
- Trace authorised use cases (procedure, not intrusive prompt surveillance)
The goal isn't to approve every possible leak, but to turn unknown risk into a controlled flow: protect → analyse → de-pseudonymise if needed.
What Safe-Doc brings
Safe-Doc doesn't replace your AI governance. It answers the operational question: "How do I summarise this file in ChatGPT without exposing names and amounts?"
- 90+ entity types detected, multinational coverage
- Zero storage: no document retained after processing
- No built-in chat: your AI queries don't pass through our servers
- Data Room for batches with consistent pseudonyms
You keep ChatGPT or Claude. You only change what the model receives.
Next step for your organisation
Map where Shadow AI is most likely (legal, M&A, HR, customer support). Pilot a pseudonymisation + AI flow on one recurring document type. Measure time saved and incidents avoided. Then scale through training and policy - not a block that won't hold on the ground.
Secure AI usage without blocking teams.