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Managers should give employees a simple operating rule: use only approved AI tools for approved tasks, protect confidential information, treat every generated answer as a draft, verify it, and keep a person accountable for the result. Unclear, sensitive, or high-impact uses should go through the organization’s review process before anyone acts on them.
The exact boundaries depend on your employer’s tools, data classifications, contracts, industry requirements, and workplace policies. The guidance below turns recommendations from the U.S. Department of Labor (DOL) and Microsoft documentation into a team conversation you can adapt; it is not a substitute for your organization’s policy or legal advice.
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Why this conversation matters
AI can speed up drafting, summarizing, brainstorming, translation, coding, and analysis. It can also omit important context, invent facts, expose information, reproduce bias, or make a confident recommendation that is unsuitable for the task. Employees need to know both sides before they use it in ordinary work.
The DOL’s October 16, 2024 best-practices announcement emphasizes transparency with workers, worker input, training, data protection, and meaningful human oversight for significant employment decisions. Its accompanying AI-literacy material puts the responsibility plainly: “While AI can accelerate work and surface helpful insights the results it produces still require thoughtful review.” Those are recommendations, not automatically binding rules in every workplace, but they provide a useful baseline for a manager’s briefing.
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Set the first boundary: approved tools and approved tasks
Tell employees which tools are allowed
Name the services your organization has reviewed, the account or workspace employees must use, and the tasks each service is approved to perform. An enterprise configuration may have access controls, retention settings, audit logs, or contractual protections that a consumer account does not. “Use AI” is not a sufficient policy; employees need a list of permitted tools and an owner who can answer questions about them.
Microsoft recommends documenting policies around an organization’s own workloads and processes. Apply that principle to every service, not just Microsoft products. A tool’s marketing description cannot establish that it is approved for your data.
Classify the task before opening a tool
Use a risk check that employees can complete in seconds. The categories below are a practical framework, not a universal legal standard.
| Task type | Typical example | Default posture | Control to require |
|---|---|---|---|
| Routine, low-stakes drafting | Reformatting a public announcement or suggesting headings | Usually suitable in an approved tool | Human edit and factual check before distribution |
| Internal analysis | Summarizing non-sensitive meeting notes or comparing public options | Use only with the organization’s approved workspace | Confirm that the input is permitted and the summary is complete |
| External or consequential output | Customer advice, financial guidance, safety instructions, or a statement representing the employer | Use cautiously; a person must validate the result | Subject-matter review, source checking, and required approval |
| Employment-impacting use | Screening applicants, rating performance, recommending discipline, or deciding promotion | Do not let AI make the decision | Follow the organization’s dedicated review process and meaningful human oversight |
If an employee cannot identify the tool, task owner, data classification, or reviewer, the safe next step is to pause and ask.
Protect information before writing a prompt
Explain what must not be entered
Every employer should publish its own “never enter” and “enter only with authorization” categories. Depending on the workplace, these may include customer records, health or financial information, credentials, private employee details, unpublished product plans, legal advice, trade secrets, security incidents, or information covered by a confidentiality agreement. Do not assume that removing a name makes data anonymous; combinations of dates, roles, locations, and events can identify a person.
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The DOL’s literacy guidance says workers should understand what information should not be entered into AI tools. Microsoft’s governance guidance stresses data minimization, consent, privacy controls, and access management. Those principles do not create one universal list: the employer and the tool configuration determine the actual boundary.
Use a prompt-safety routine
- Minimize. Remove fields that are not needed for the task. Ask whether the model can work from a short, synthetic example instead of a real record.
- Classify. Check the company’s data label or handling rule before pasting text, uploading a file, or connecting a data source.
- Confirm authorization. Make sure the approved tool, account, plug-ins, and integrations are covered for that data and purpose.
- Limit the result. Request only the information needed, and do not ask the system to infer sensitive traits or hidden personal circumstances.
- Clean up. Follow the organization’s retention and deletion rules for prompts, uploaded files, exports, and conversation history.
If a prompt contains information an employee would not email to the wrong recipient, it deserves a policy check before submission.
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Treat every AI response as a draft
AI output can be fluent and still be wrong, incomplete, out of date, or poorly matched to the question. The DOL advises workers to cross-check factual claims against trusted sources and review for completeness, logical errors, and fit for purpose. Microsoft’s Copilot documentation likewise warns that generative-AI responses are not guaranteed to be fully factual and says users should exercise judgment before sharing them.
A five-step review workflow
- Frame the task. State the audience, objective, constraints, date, jurisdiction, and what a correct answer must contain. A precise request makes errors easier to spot.
- Generate a first draft. Ask for assumptions, uncertainty, missing information, and the sources or calculations behind material claims. Treat those explanations as leads to check, not proof.
- Verify important facts. Open the authoritative policy, contract, specification, dataset, or primary source yourself. Check names, dates, figures, quotations, citations, formulas, code behavior, and links.
- Review the whole result. Look for omitted exceptions, invented details, biased wording, unsafe instructions, privacy exposure, and conclusions that do not follow from the evidence. Test code and calculations in an appropriate environment.
- Approve and record. Edit the draft, obtain the required subject-matter or manager approval, and retain the final source material or review record when the task requires an audit trail.
For routine internal prose, the review may be quick. For safety, legal, financial, customer, or employment content, the reviewer should have the authority and expertise to reject the output.
Keep a person responsible for decisions
AI can assist with a decision; it should not silently become the decision-maker. The DOL’s literacy material states: “Workers remain responsible for the decisions and outputs they produce with AI tools and should avoid treating AI responses as final or authoritative without review.” Responsibility stays with the employee and manager who use, approve, or act on the result.
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Use extra safeguards for employment matters
Meaningful human oversight is especially important when a system could affect hiring, promotion, pay, scheduling, performance ratings, discipline, termination, accommodations, or access to opportunities. A manager should be able to explain what evidence was considered, what the AI did, what a person checked, and why the final decision was justified without relying on an unexplained score or profile.
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Make questions and reporting part of the process
Employees should know where to ask before using a new tool or data type and where to report an error after use. The DOL calls for worker input and transparency; Microsoft’s responsible-AI guidance also emphasizes governance and feedback. Neither source requires one universal channel. Your organization might use a manager, an information-security mailbox, a privacy officer, an AI governance group, a compliance hotline, or an incident system.
Ask employees to report
- A tool that is not on the approved list or has unexpected access to company data.
- A prompt or response that appears to expose confidential information.
- An invented citation, discriminatory pattern, unsafe recommendation, or materially incorrect answer.
- A decision that someone is pressuring them to delegate to AI without the required human review.
- A use that does not fit the written policy or a situation where the policy is unclear.
Reporting should be treated as risk control, not as an admission of misconduct. Managers should preserve the relevant prompt, output, file, date, tool name, and people involved when policy permits, then escalate through the designated process.
Teach practical AI literacy, not just a prohibition
Employees do not need to use AI, but anyone who does should be able to frame a task, evaluate an answer, and handle information responsibly. A short exercise can cover:
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- Prompt framing: identify the objective, audience, constraints, acceptable sources, and required format.
- Iterative use: ask the tool to expose assumptions or propose alternatives, then refine the request instead of accepting the first response.
- Evidence checking: distinguish a cited, verifiable fact from a plausible-sounding statement.
- Output hygiene: remove hidden personal data, unsupported claims, unnecessary identifiers, and language that could mislead a reader about human authorship or review.
- Escalation: recognize when the task is high-impact, the data is restricted, or the answer is uncertain.
Understand product-specific behavior before promising privacy
Microsoft states that Microsoft 365 Copilot surfaces organizational data that a user already has permission to view, and that prompts and responses are stored as Copilot activity history. Those statements describe Microsoft’s services and documentation, marked last updated August 18, 2026; they do not establish how another AI service stores prompts, trains models, handles administrators’ access, or responds to deletion requests.
Before deployment, managers should ask the tool owner for the actual tenant configuration, retention period, connector permissions, logging, human-review controls, and approved data classes. If the answer is not documented, do not promise employees that their prompts are private or temporary.
A manager’s ready-to-use team message
Adapt this wording to your policy and replace “our review process” with the real channel:
“Use only the AI tools and tasks our organization has approved. Follow our data rules, and do not enter sensitive or confidential information unless the tool and use are explicitly authorized. Treat AI responses as drafts: check important facts against reliable sources, review for missing context and errors, and use your own judgment before sharing or acting. You remain accountable for work you produce. Do not use AI as the decision-maker for consequential employment matters; escalate uncertain, sensitive, or high-impact cases through our established review process. Tell us when the tool produces an error or creates a concern.”
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This wording is a synthesis of the DOL and Microsoft guidance, not a quotation from either source. It should be shortened or expanded to match the employer’s actual tools, classifications, approvals, and reporting route.
Apply the rules to common situations
“Can I summarize customer emails?”
Only if the approved workspace is authorized for that customer information. Remove unnecessary identifiers, check the resulting summary against the original thread, and obtain the normal approval before sending advice or commitments to the customer.
“Can I paste a confidential draft to improve the writing?”
Not unless the tool, account, and data handling are explicitly approved for that confidentiality level. Use a synthetic example or an organization-approved editing feature when authorization is absent.
“The model gave me a policy citation.”
Open the policy yourself and confirm the section, version, effective date, exceptions, and jurisdiction. If you cannot verify it, do not cite or rely on it.
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“Can AI rank applicants or employees?”
Do not proceed on an informal basis. Employment-impacting use requires the organization’s dedicated review, documented criteria, and meaningful human oversight; an AI score cannot replace accountable decision-making.
“The output looks biased or unsafe.”
Stop using the result, preserve the relevant details if permitted, notify the designated channel, and do not conceal the issue by quietly rewriting the output if the incident could affect people, customers, security, or compliance.
What managers should put in the written reminder
- The approved tools, account types, and permitted use cases.
- Data classes that are prohibited, restricted, or allowed only with authorization.
- The reviewer or approver required for external, regulated, safety-related, financial, legal, customer, or employment outputs.
- The minimum verification expected for facts, calculations, code, citations, and translations.
- The rule that employees remain accountable for decisions and deliverables.
- The question and incident-reporting channel, including what information to preserve.
- The date of the policy, its owner, and how employees will be notified of changes.
Review the reminder when tools, connectors, retention settings, data classifications, or applicable requirements change. A clear, current rule is more useful than a broad promise that AI is either always safe or always forbidden.
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