How to Use AI at Work Without Exposing Confidential Information
A safe-use rule for deciding what can enter an AI system, what must stay out and what to do after a mistake.
- Published
- 25 July 2026
- Reviewed
- 25 July 2026
- Next review
- 25 October 2026
- Reading time
- 10 minutes
On this page
Answer First
The practical answer
Do not paste personal data, client material, unpublished financial information, source code, credentials or other confidential content into an AI tool unless your organisation has approved that exact tool and use, the data is permitted, and the necessary contract, access, retention and security controls are in place. Redaction can reduce risk but is not a substitute for approval because context may still identify a person or reveal a secret.
Who This Affects
Use this guide if any of these describe you
- Employees using public or employer-provided generative AI services
- Managers introducing AI into workflows containing client, worker or commercial data
- Professionals subject to confidentiality, privacy, security or record-keeping duties
Evidence Strength
StrongEditorial format
GuidePortfolio role
Evergreen decision pageKey takeaways
- A paid account or private-looking interface does not prove that a use is approved or confidential.
- Classify the information, tool and purpose before entering content, and use synthetic data for learning where possible.
- If sensitive material is entered by mistake, stop, preserve the facts and report it through the normal incident route promptly.
Why ordinary copy and paste now creates a disclosure route
Generative AI services can receive prompts, uploaded files, connected application data and feedback. The handling of that material depends on the service, account, configuration, contract and region. Consumer and enterprise versions should not be treated as interchangeable.
The risk is wider than model training. Access controls, logs, retention, third-party processing, connectors and generated output can all expose or reproduce information.
Classify before you prompt
Ask who owns the information, who it identifies, what duty applies and whether the exact system is authorised. The ICO requires organisations processing personal data through AI to meet data-protection principles, while NIST and the NCSC emphasise governance and security across the system lifecycle.
- Public: already lawfully published and safe to reuse for this purpose.
- Internal: not public, but approved policy may permit use in a controlled enterprise system.
- Confidential: client, commercial, legal, source-code or security material that needs explicit controls.
- Personal or sensitive: information about identifiable people, with additional legal and ethical duties.
- Restricted: credentials, secrets, regulated records or high-consequence information that must not enter the tool.
Use the minimum-data pattern
Start with a blank or synthetic example. If real data is necessary and permitted, remove fields that the task does not need, replace identifiers consistently and work inside the approved environment. Check that generated output does not reveal source material to a broader audience.
For recurring use, ask the system owner for a documented data-flow view covering provider access, retention, deletion, locations, logging, connectors and incident response.
What to do if information was entered by mistake
Do not hide the event or compound it by repeatedly testing whether the material can be recovered. Record the service, account, time, content category, recipients and action taken without copying the sensitive material into another unsafe channel.
Report promptly to the security, privacy or legal route named by your employer. The responsible team can assess deletion options, credential rotation, contractual notification and any regulatory duties. This article is general information, not legal advice.
Related profession guidance
See how this reaches the work you do
Sources
Read the evidence behind this guide
- Regulator guidanceCurrent regulator guidance, accessed 25 July 2026Information Commissioner's Office: Guidance on AI and data protection
UK data-protection guidance for organisations using AI to process personal data.
- Primary report26 July 2024National Institute of Standards and Technology: Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile
Cross-sector profile covering generative AI risks and suggested risk-management actions.
- Official guidance27 November 2023UK National Cyber Security Centre: Guidelines for secure AI system development
- Official guidance10 February 2025Government Digital Service: AI Playbook for the UK Government
Public-sector guidance with practical principles for safe, effective and secure AI use.
Reviewed and updated
Change log
First publication, checked against the listed primary and official sources.
Follow changes affecting your role
Keep this topic in your saved list
WorkChanged uses a local preference until a verified alert service is connected.
Save this preference on this device. Email alerts are not connected yet.
A focused return path
