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GDPR and workplace AI 7 min read

GDPR and employee use of AI tools: a practical rollout guide

What a GDPR-ready rollout of AI tools takes: controller responsibility, a DPIA where needed, data minimisation, clear guidance and a highlight before anything is sent.

ChatGPT5
Summarise my notes from this performance review into a short write-up.
Paste the notes below and I'll turn them into a concise summary.
ChatGPT can make mistakes. Check important info.

The example above is interactive. Click a highlighted value to see what you can do with it.

An organisation rolls out an AI tool. There is a data processing agreement, instructions have gone round and the first week goes smoothly. Then someone in support pastes a customer email with a name and an account number into the tool, because that is the quickest way to draft a reply. What makes the rollout GDPR-ready is not the contract but what you put in place after it: purpose limitation, data minimisation, a DPIA where the risk is high, clear guidance for employees and a highlight before personal data goes into the tool.

Controller responsibility in practice

When your employees use an AI tool for work purposes, your organisation is the controller for the personal data they put into prompts. That means the familiar obligations apply: lawful basis, purpose limitation, data minimisation and the rest.

The challenge is that AI tools have made it much easier to accidentally process personal data at scale. A single support team member can run hundreds of prompts per day, each potentially containing customer names, contact details or account information.

Treat AI use as an everyday working risk as well as a procurement risk. The vendor's terms matter, and so does what employees do with the tool.

DPIA: when do you need one?

A DPIA is most relevant when the use case is likely to create high risk for individuals. Practical triggers include:

  • Systematic processing of special category data (health, religion, political views)
  • Processing at scale that would not otherwise be subject to oversight
  • Combining datasets in ways that create new risks

Not every use of ChatGPT requires a DPIA, but using it to process customer health records or employee performance data very likely does. As a starting point for your risk assessment, write down which categories of data should never go into public AI tools.

Data minimisation: the practical approach

The GDPR principle of data minimisation means using only the personal data necessary for the purpose. In a prompt, that comes down to:

Employees cannot do this on autopilot. They need a tool that shows them what is sensitive in their prompt before they submit it, so they can make the right choice there and then.

ChatGPT5
Summarise my notes from this performance review into a short write-up.
Paste the notes below and I'll turn them into a concise summary.
ChatGPT can make mistakes. Check important info.
Hover over or tap a highlighted value to mask or delete it before the draft reaches anyone.

Minimisation also covers documents. A case file, a personnel file, a client report: the same names, dates of birth and account numbers turn up in files that get pasted or attached. A tool that opens the document, highlights what is sensitive and lets someone redact it before sharing covers that route too.

PreviewAnonymise (4)
The desktop app highlights sensitive fields in a document so you can redact them before you share it or paste it into an AI tool.

Keep records of training, controls and reviews without turning the rollout into surveillance.

What employees need to know

They should know:

  • Which tools are approved for which use cases
  • What categories of data are out of scope for AI tools (special categories, confidential client data, credentials)
  • How to anonymise or mask prompts when working with sensitive content
  • Where to escalate if they are unsure

The first bullet assumes you can answer it. Most organisations cannot, until they can see which AI tools people have opened, not just the two or three that were formally rolled out:

AI register
AllowedUnder reviewNot allowedAll tools
Search by tool, vendor, domain or former name…
1,012 tools
DeepSeek
Critical · 90/100
Not allowed
Otter.aiNew
High · 68/100
No decision yet
Grok
High · 67/100
Not allowed
ChatGPT
High · 62/100
Allowed
Perplexity
Medium · 55/100
No decision yet
HeyGen
Medium · 53/100
No decision yet

Every tool, scored for risk

Over 1,000 AI tools, each scored from Low to Critical. Nothing is approved or blocked until someone decides.

More about AI Governance

Each tool appears with a risk score already attached, so "which tools are approved" stops being a guess and becomes a decision you can point to.

A good policy is short, specific and tied to real tasks. Write rules employees can remember in the middle of their work, not a 20-page document they sign once and never read again.

So do not start with the document; start with the list of tools people actually open. Then write the policy for that list.

Portrait of Rens Timmermans from BeeSensible

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