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Managers should give employees a simple rule: use only organization-approved AI tools for permitted tasks, protect information, treat every response as a draft, verify important claims, and keep a person accountable for the result. When a task involves sensitive data, a consequential decision, or an uncertain output, stop and use the employer’s review or escalation process.
The exact boundaries depend on your employer’s tools, data classifications, contracts, sector and applicable requirements. The guidance below turns U.S. Department of Labor recommendations and Microsoft product documentation into a conversation a manager can adapt; it is not a substitute for your organization’s policy or legal review.
The message employees need to hear
A manager can state the expectation in one paragraph:
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This wording is a practical synthesis, not a quotation from a government agency or vendor. Replace “approved,” “sensitive,” and “review process” with the terms in your own policy.
Why a blanket “AI is allowed” rule is not enough
AI risk changes with the task, the information supplied, the system configuration and the consequence of an error. Drafting a public-facing outline from public facts is different from summarizing a personnel file, recommending a candidate, or sending an answer to a customer without review. The U.S. Department of Labor’s October 16, 2024 workplace-AI best-practices announcement emphasizes transparency, worker input, training, data protection and meaningful human oversight for significant employment decisions. Those are recommendations, not automatically binding law in every workplace.
The Department’s AI-literacy material also treats literacy as more than knowing how to write prompts. Employees should understand organizational rules, recognize that risks vary by task and sector, protect sensitive information, evaluate outputs and remain accountable for decisions and work produced with AI. Microsoft’s responsible-AI and deployment guidance similarly recommends policies tailored to an organization’s workloads and processes rather than a universal permission.
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Name the tools and environments
Tell employees which services are approved, how they sign in, and whether a work-managed account is required. An “approved tool” should mean more than a familiar brand: it should be the specific service, tenant, extension or integration reviewed by security, privacy and legal teams. If a consumer site and an enterprise deployment have different retention, access or contractual terms, list them separately.
Define permitted tasks
Policies should identify examples of allowed, restricted and prohibited work. An employee might be allowed to brainstorm headings for a public presentation, but not to paste an unreleased presentation containing customer names. A coding assistant may be permitted for a repository that has been cleared for that use, while source code covered by a client agreement may require a separate approval. State whether AI may draft communications, summarize meetings, translate text, analyze data, generate code or act through connected systems.
Explain who can approve an exception
Employees should know whether an exception requires a manager, information-security officer, privacy officer, human-resources reviewer or another named role. “Ask someone if unsure” is not a process unless the policy gives a channel and an expected response. Make clear that a manager’s informal permission cannot override contractual, privacy, security or regulatory restrictions.
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Protect information before it reaches an AI system
Use the employer’s data classification
Connect AI instructions to the classifications employees already use, such as public, internal, confidential and restricted. For each class, state whether it may be entered, under what approved configuration, and whether extra controls or approval are required. The Department of Labor advises workers to understand what information should not be entered into AI tools; it does not prescribe one universal list because the correct categories depend on the employer and context.
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- Personal data about employees, applicants, customers, patients or other identifiable people.
- Passwords, authentication tokens, encryption keys and other security credentials.
- Nonpublic financial results, pricing, strategy, merger information or trade secrets.
- Client or partner information subject to a contract, nondisclosure agreement or professional duty.
- Unreleased code, vulnerability details, incident records and internal investigation material.
- Health, biometric, employment-performance or other specially protected information.
This list is an example for training, not a replacement for your classification scheme. Redaction can reduce exposure, but it does not automatically make a use acceptable: combinations of seemingly harmless details can identify a person or reveal confidential context.
Minimize what you provide
Give the system only the information needed for the permitted task. Remove names, direct identifiers and unnecessary fields where the workflow allows it. Do not assume that deleting a chat later erases copies, logs, backups or downstream records. Ask the tool owner how prompts, files, outputs and telemetry are retained, who can access them and whether they are used for service improvement.
Teach employees to treat output as a draft
Check facts against trusted sources
The Department of Labor advises workers to cross-check factual claims against trusted sources and review an answer for completeness, logical errors and fitness for purpose. Verification should match the stakes: a minor wording suggestion may need a quick read, while a legal, medical, financial, safety or customer-impacting statement needs authoritative source checking and, where required, subject-matter review.
Microsoft’s Copilot documentation states, “The responses that generative AI produces aren’t guaranteed to be 100% factual.” That warning applies to Microsoft’s described services; other tools may have different behavior and terms, but no system should be treated as inherently authoritative.
Look for omissions and misleading confidence
An answer can be grammatically polished yet incomplete, based on an outdated rule, or wrong about what the question means. Employees should ask:
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- What important facts, exceptions or stakeholders are missing?
- Did the system confuse a person, date, version, jurisdiction or unit?
- Can I reproduce the cited result from a reliable source?
- Does the tone imply certainty that the evidence does not support?
- Would a reasonable reader misunderstand this if the AI caveat were removed?
Keep evidence of the human review
For consequential work, preserve the sources checked, material edits and approval record required by the team’s normal process. Do not present an AI-generated citation, calculation or quotation as verified merely because it looks plausible. If the tool cannot show where a claim came from, obtain the evidence independently or remove the claim.
Keep a person responsible for decisions and outputs
Employees remain responsible for the decisions and work they produce with AI. The Department of Labor’s AI-literacy material puts it plainly: “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.” Accountability includes selecting an appropriate tool, protecting data, checking the result, correcting errors and obtaining required approval.
Do not delegate consequential employment decisions
Managers should not let an AI system make the final call on hiring, promotion, discipline, termination, compensation, scheduling access to opportunities or other significant employment matters. The Department of Labor recommends meaningful human oversight for significant employment decisions. A person must have the authority, information and time to question the system, investigate the underlying facts and make an independent decision; merely clicking “approve” is not meaningful oversight.
Watch for inferences about people
Microsoft describes workplace harms as AI inferences or evaluations about an employee’s performance, attitude, internal or emotional state or personal characteristics, and says it restricts relevant uses in its Copilot scenarios. Treat that description narrowly as Microsoft service documentation, not as a complete legal definition for every employer. In any system, do not infer sensitive traits or hidden mental states from writing, browsing, keystrokes, attendance or other indirect signals without a documented, lawful and reviewed purpose.
Use a task-risk check before starting
A short check helps employees decide whether to proceed, seek approval or stop. The categories below are an operational framework derived from the distinctions in the government and vendor guidance, not a formal scoring standard.
| Question | Lower-risk indication | Higher-risk indication | Action |
|---|---|---|---|
| What information will be supplied? | Public or deliberately anonymized material | Confidential, personal, regulated or contract-restricted data | Use only an approved configuration; obtain the required data approval or do not proceed |
| What will the output do? | Private brainstorming or a reversible draft | Advice, a customer commitment, a filing, code in production or an employment action | Require source checking and the normal subject-matter or managerial review |
| How severe is an error? | Minor wording or formatting inconvenience | Safety, legal, financial, privacy, access or reputational harm | Escalate uncertainty and document the review |
| What tool context applies? | Organization-managed tool with documented controls | Unreviewed consumer service, plug-in or connected action | Stop and confirm approval, retention and permissions before use |
A practical workflow employees can follow
- Frame the task. Write down the intended result, audience, deadline and consequence of an error. Decide whether AI is necessary; employees are not required to use it merely because it is available.
- Check the policy. Confirm the exact tool, account and task are approved. Check data classification, retention terms, connected applications and any sector or client restrictions.
- Prepare the input. Minimize data, remove unnecessary identifiers and preserve the context needed for an accurate answer. Never paste secrets or restricted material without explicit authorization.
- Generate a draft. Give clear instructions and ask the system to identify assumptions or uncertainty. Do not treat a confident tone as evidence.
- Verify. Compare factual claims, calculations, quotations, citations and dates with trusted primary or internal sources. Test code and inspect summaries against the original material.
- Apply human judgment. Rewrite for the audience, correct omissions and decide whether the result actually meets the task. Obtain specialist or managerial approval when the normal workflow requires it.
- Record and escalate. Keep the review evidence required for the work. Report a material error, data exposure, biased or unsafe behavior, or unexpected action through the organization’s stated channel.
How managers should handle questions and incidents
When an employee asks, “Can I put this into the tool?”
Ask what the data contains, which tool and account they plan to use, what the output will be used for and what policy classification applies. If any answer is unclear, pause the task and route it to the designated owner. Do not approve by intuition or because the same data was previously shared in another context.
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When the output is wrong or biased
Have the employee preserve the prompt, relevant input, output and date where policy permits, then assess whether anyone relied on it. Correct the work through the ordinary quality process, notify affected stakeholders if necessary and report the behavior to the tool or risk owner. A polished answer that contains a harmful inference is an incident, not just a writing problem.
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When data may have been exposed
Tell the employee not to delete evidence or continue experimenting. Follow the organization’s incident-response instructions immediately so security and privacy teams can assess access, retention and notification duties. The manager should avoid promising that no harm occurred before that assessment.
When employees disagree with an AI-enabled process
Invite the concern and worker input rather than treating resistance as misuse. The Department of Labor’s workplace-AI recommendations emphasize transparency and worker participation. Explain the purpose, limits, review rights and escalation path, and record unresolved concerns for the responsible governance team.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Microsoft Copilot details managers should state carefully
Microsoft says Microsoft 365 Copilot surfaces organizational data that a user already has permission to view, and that prompts and responses are stored in Copilot activity history. Those statements describe Microsoft’s services and can vary with licensing, tenant configuration and product changes. They are not a basis for assuming that every AI service has the same permissions or retention behavior.
Before enabling a Copilot scenario, the organization should review identity and access controls, sharing permissions, retention settings, auditability, connected data sources and the applicable Microsoft documentation. Employees should still avoid entering information that policy forbids, even when they are using a work-managed account. A managed account limits some risks; it does not remove the need for data minimization, verification or human accountability.
Give employees training that matches the work
A useful program teaches people to frame a task, iterate on a draft, evaluate claims and handle information responsibly. Use examples from the team’s actual workflows: a public announcement, an internal summary, a customer response, a code change and a personnel decision should produce different approval requirements. Include practice in spotting missing context, unsupported citations, invented details and inappropriate certainty.
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Training should also explain what employees are not expected to do. They do not need to use AI for every task, disclose confidential material to obtain a faster draft, or accept an automated recommendation to meet a productivity target. The goal is competent, controlled use—not maximum usage.
Manager checklist for a team conversation
- Name the approved tools, accounts and permitted tasks.
- Show where the data-classification and retention rules live.
- Give concrete examples of information that must not be entered without authorization.
- Require verification against trusted sources before sharing or acting.
- State who owns the final decision and which approvals apply.
- Explain the special review required for employment, safety, legal, financial, privacy or customer-impacting work.
- Provide one clear channel for questions and one for suspected errors or unsafe use.
- Invite worker feedback and explain how concerns will be recorded and answered.
- Revisit the guidance when tools, configurations, contracts or applicable requirements change.
Frequently Asked Questions
Does an employer have to let every employee use AI?
No. The guidance supports informed, approved use; it does not require an employer to provide AI or require an employee to use it. A policy can prohibit particular tools or tasks when the organization cannot manage their data, quality or legal risks.
Is a work account enough to make a prompt safe?
No. A managed account may provide stronger access and retention controls, but employees still must follow data-classification rules, use the approved configuration and avoid information the policy prohibits.
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Treat the claim as unverified. Check it against an authoritative source or ask the responsible subject-matter reviewer; remove it if it cannot be substantiated.
Can a manager use an AI ranking as the final hiring decision?
The Department of Labor guidance calls for meaningful human oversight in significant employment decisions. An AI ranking should not replace an independent, documented human decision and the review required by the employer’s policy and applicable requirements.
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