Use AI tools at work only within an agreed purpose, with suitable data controls and someone accountable for the result. Drafting an internal agenda is different from screening applicants or sending customers advice. I would judge each use separately rather than approve or ban everything carrying an AI label. The following questions turn that distinction into a workable workplace policy.
1. Which AI tools and accounts are approved?
Ask your manager or IT team which services, account types and features may be used. Approval for one business workspace does not necessarily cover a personal account with the same provider. Record permitted tasks and prohibited information. Staff need a clear route to request approval, otherwise a rule to use AI responsibly leaves too much undefined.
2. Is the task suitable for generated output?
Start with work where errors can be detected and corrected before anyone relies on them. A draft outline and an automated hiring recommendation have different consequences. Consider whether the person reviewing the result has the expertise and time to challenge it. Faster production is not useful when verification becomes slower than completing the original task.
3. What information would leave the organisation?
Identify personal data, confidential business information and material governed by customer contracts. Check the provider’s processing, retention, access and training terms before entering it. The NCSC advises against submitting sensitive information to public language models.
Public reading on Local News Point and uploading a private client file are different activities. Keep that boundary explicit in the policy, including file attachments and connected storage.
4. Who checks accuracy and missing context?
Assign a reviewer for facts, calculations, citations and tone. AI can produce plausible errors or invent references, so a polished answer is not a finished deliverable. Compare important claims with the original evidence. For a summary, check what was omitted as well as what was included. Keep the source document available to the reviewer.
5. Could the process treat people unfairly?
Look carefully at recruitment, performance assessment and customer eligibility. An apparently neutral output can reflect unsuitable assumptions or biased inputs. Test the process against its actual purpose and people affected. Seek specialist advice before adopting consequential decision systems; casual human approval at the end is not a substitute for proper assessment, challenge and governance.
6. What should staff and customers be told?
Explain the permitted uses, responsibilities and reporting routes to workers. Acas recommends consultation with staff and representatives, and checking whether expectations change employment terms. Decide when customers or recipients should be told about AI involvement, taking account of the service and applicable obligations.
A mention on Press Hubs does not set your organisation’s disclosure policy. Put the agreed approach into instructions people can follow.
7. What training is needed?
Teach staff how to choose suitable inputs, recognise uncertainty, protect information and verify results. Include the tools they actually use rather than a demonstration built around impressive but irrelevant prompts. Explain how to report mistakes without hiding them. Acas specifically recommends checking outputs for accuracy, tone and bias, with training where needed.
8. What can the tool do beyond producing text?
Separate drafting from permission to send messages, modify records or make purchases. Give connected services only the access needed and require approval before consequential actions. Review who can share conversations or retrieve stored files. An assistant that can search a document is not automatically entitled to publish its contents.
General commentary through Weekly Journal is separate from authorising those actions. Permissions should follow the task, not the product’s available features.
9. How will you know whether it helps?
Include ordinary and difficult cases in the trial, not only examples chosen because the tool handles them well. Record the version, settings and review process used so the comparison has meaning. Reassess after important changes, and keep a workable alternative for staff when the service is unavailable or performs poorly.
Run a bounded trial and compare completed work, correction time and errors against the existing process. Include subscription and oversight costs. Keep an owner who can suspend an unsuitable use. Continue only where the evidence shows a useful result without unacceptable information, employment or operational risks.
This article provides general workplace information; obtain appropriate advice for consequential employment, data protection or legal decisions.
