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Check your employer’s or client’s rules first. When disclosure is required—or simply useful—say which work involved AI, what the tool did, and what you personally directed, checked, changed, or decided. Describe only the steps you actually took, and make clear that you reviewed and take responsibility for the version you share.
Start with the rule that applies to your work
Disclosure expectations depend on the organization, task, audience, and sometimes jurisdiction. Check your employer’s AI policy, approved-tool list, data-handling rules, and any client, funder, or publication requirements before sharing details or using AI for the task. The CDC advises authors of scientific work to follow their organization’s and collaborators’ requirements; that guidance is a useful model, not a universal rule for employees. CDC guidance for authors
There is no universal requirement established here that every employee everywhere disclose every AI interaction. Government rules can be narrower: New Jersey, for example, requires prominent disclosure for certain state systems that interact with residents or inform decisions. OECD describes a varied policy landscape, including U.S. state requirements focused on areas such as recruitment and electronic monitoring. Those examples should not be treated as rules for every private workplace. OECD report on AI in the workplace New Jersey AI guidance
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What a useful disclosure says
A concise disclosure gives a reader enough context to understand the AI’s role and your own. CDC’s scientific-writing framework organizes this as “Content Affected + Action Taken + AI Tool + Purpose of AI Use + Human Oversight.” Its guidance says: “Disclosure statements should include which AI tool(s)/platform were used, including model type and version, where in the work they were used, and the extent of human oversight (e.g., review and validation).” CDC guidance for authors
- Work affected: name the document, section, analysis, or task.
- AI action and purpose: explain whether it brainstormed, summarized, drafted, edited, analyzed, or suggested formulas, and why you used it.
- Tool details: name the tool and model or version if known and relevant.
- Your contribution and oversight: state what you directed, checked, tested, revised, or decided.
Use this adaptable structure, removing any clause that does not accurately describe what happened: “I used [tool/model, if known] to [specific task] for [purpose]. I [describe your actual contribution: selected inputs, directed the draft, checked facts, edited, tested, or made the final decision]. I reviewed the result and am responsible for the version I’m sharing.”
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For scientific work, CDC gives an example: “Portions of the introduction and discussion sections were edited using [Name of AI tool] [model/version, if available] [(manufacturer, location)] for language refinement; authors reviewed and approved all edits.” That example is aimed at scientific authors; adapt its level of detail to your workplace’s rules and audience rather than treating it as a mandatory employee format. CDC guidance for authors
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Separate the task the AI performed from the choices and checks you made. NIST’s AI Use Taxonomy offers shared terminology for describing human-AI activities and outcomes; it does not prescribe a workplace credit formula. NIST AI Use Taxonomy
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Choose the verbs that fit your actual work: framed the task, selected source material, supplied instructions, compared alternatives, applied domain judgment, checked facts, tested calculations, revised language, reviewed accessibility, or approved the final version. Do not claim checks you did not perform, and do not describe AI-generated material as entirely unaided human writing.
Microsoft’s responsible-AI guidance recommends review and editing, reminders about possible inaccuracies, and accountability for final content. It states: “Remind people that they’re accountable for the final content when they’re reviewing AI-generated content.” This is vendor guidance, not employment law. Microsoft responsible-AI guidance
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Examples you can adapt
These are original examples, not quotations from policy documents. Adjust them to match the tool, task, checks, and disclosure rules that actually apply.
- Meeting notes: “I used an AI assistant to organize my meeting notes into a first draft. I checked names and decisions against my notes, rewrote the action items, and approved the version sent to the team.”
- Spreadsheet formulas: “I used an AI tool to suggest spreadsheet formulas. I tested them against sample rows and corrected two errors before using them.”
- Planning: “I used AI to brainstorm options. I chose the recommendation after checking it against the project requirements.”
These examples are specific about both roles: the tool’s contribution and the person’s decisions or verification. If someone asks, be ready to explain what part of the work involved AI and what checks you performed.
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Match the detail to the audience and risk
A note to a teammate, a client-facing deliverable, and work that affects a decision may call for different levels of detail. Before drafting a disclosure, consider these factors:
- Audience and stakes: Is the work internal, client-facing, public, or used to inform a decision?
- Applicable rules: What do organizational, client, funder, publication, or relevant legal requirements specify?
- Extent of AI involvement: Was AI used for a small brainstorm, language edits, substantial drafting, or analysis?
- Review performed: What did you actually verify, test, edit, or approve?
- Information sensitivity: Was the tool approved for the data involved?
OECD notes that AI use can be difficult to detect without explicit disclosure; in a 2024 report, it cites a 2023 finding that 17% of adults in the United Kingdom could often or always tell when they were using AI. That figure concerns the stated UK population and measure, not workers generally. OECD report on AI in the workplace
Protect workplace information while disclosing
Be candid about AI use without exposing confidential material. Use only tools approved for the task and follow your organization’s rules for personal, confidential, proprietary, or regulated information. A public AI service may handle data differently from a tool managed within an organization’s environment.
The U.S. Consumer Product Safety Commission’s policy illustrates this distinction: it tells personnel to critically review and edit in-tenant AI outputs before formal use and not to share confidential or proprietary information with public AI systems. That is an agency policy, not a rule for all workplaces; check your own organization’s approved tools and data classifications. CPSC policy on generative AI use
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