Yes—but only through an agency-authorized, risk-managed deployment. A federal employee should not paste sensitive government information into an ordinary public chatbot simply because the service is available. The agency must classify the task, protect the data, approve the vendor and contract, meet privacy, cybersecurity, records-management and civil-rights requirements, and keep people accountable for the result.
Low-risk work such as drafting, summarizing or brainstorming can be permitted with appropriate safeguards. Uses that influence benefits, eligibility, employment, law enforcement, safety, rights or access to critical services require substantially stronger controls and may have to be stopped if the agency cannot demonstrate compliance.
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What “private AI chatbot” means in government
In this context, a private AI chatbot is a commercial or contractor-operated generative-AI service that an agency accesses under an enterprise agreement, an approved government environment or another controlled arrangement. “Private” does not automatically mean secure, confidential or government-approved. A paid account, a business plan or a vendor’s promise that it does not train on prompts is not a substitute for an agency authorization.
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The key distinction is between an authorized service and an employee using an unapproved public website. An authorized deployment has defined users, permitted purposes, data classifications, technical controls, contractual terms, logging, incident procedures and an accountable program owner. The same underlying model could be acceptable for one task and prohibited for another because the data, impact or legal obligations differ.
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What federal policy permits—and what it does not
Federal policy supports access to secure commercial AI capabilities for experimentation and routine, low-risk work when safeguards are in place. Agencies still have to comply with all applicable privacy, cybersecurity, records, civil-rights, procurement, intellectual-property and sector-specific requirements. The authority to use a service comes from the agency’s approval and controls, not from the chatbot being commercially available.
OMB Memorandum M-25-21 requires agencies to document implementation of its minimum practices. OMB Memorandum M-25-22 addresses the acquisition and use of AI with personally identifiable information (PII), including early and ongoing involvement by the Senior Agency Official for Privacy (SAOP). These memoranda primarily govern federal executive-branch agencies; state, local, tribal and territorial governments may follow different statutes, procurement rules, public-records laws and privacy requirements.
Why the question matters now
Government use is expanding quickly. The U.S. Government Accountability Office reported that selected agencies listed 282 generative-AI use cases in 2024, up from 32 in 2023—an increase of about ninefold. Across those inventories, total AI use cases rose from 571 to 1,110. Growth does not eliminate the need for approvals; it makes consistent governance more important.
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When an agency may use a chatbot
Low-risk administrative and analytical work
Examples can include producing a first draft from public material, summarizing a non-sensitive report, generating meeting questions, translating text that is already public, brainstorming code comments or creating a checklist. The agency should still use an approved account, avoid restricted data, verify every material output and retain records when the work is part of an official transaction.
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High-impact or safety-impacting work
Stronger controls apply when an output can affect a person’s rights, benefits, eligibility, employment, housing, immigration status, law-enforcement treatment, health or safety, or access to a critical government service. OMB’s minimum practices call for impact assessments, testing, documentation, monitoring and reporting for rights-impacting and safety-impacting AI. A chatbot may assist a qualified employee, but it cannot quietly become the decision maker.
Before deployment, the agency should define the decision, identify affected people, test for inaccurate or discriminatory results, establish human review and override procedures, and specify when use must be suspended. If those controls cannot be demonstrated, the use case should not proceed.
Experimentation and pilots
A pilot can be lawful when it is explicitly approved, bounded in scope and monitored. Use synthetic, de-identified or public data where possible; limit the user group; set a time period; and document success criteria, known limitations, incidents and a shutdown plan. “It is only a test” does not authorize sending real PII or classified, law-enforcement-sensitive or procurement-sensitive information to a vendor.
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Authorization is an agency process, not an individual purchasing decision. The State Department provides a concrete example: personnel may not create official AI-service accounts unless the terms of service have been approved by legal authorities and the service is authorized by the appropriate policy components.
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- Identify the business owner. Name the office responsible for the mission need, budget, users, output quality and ongoing monitoring.
- Describe the use case. Record the task, intended users, workflow, data elements, expected benefit, jurisdictions affected and whether an output is advisory or determinative.
- Classify the data. Mark whether prompts or uploaded files contain PII, confidential or law-enforcement information, procurement-sensitive material, controlled unclassified information, intellectual property or other restricted content. Set a rule for what may never be entered.
- Assess impact. Determine whether the use is routine, rights-impacting, safety-impacting or otherwise high impact. Document affected populations, foreseeable harms, bias risks and the human decision point.
- Obtain privacy review. When PII is involved, involve the SAOP early and continuously, as required by OMB M-25-22. Complete the agency’s privacy documentation and verify lawful collection, use, disclosure and retention.
- Obtain security and legal review. Check identity management, encryption, access controls, vulnerability management, incident reporting, records obligations, accessibility, civil-rights requirements and the vendor’s terms.
- Approve the acquisition and contract. Procurement officials should make the permitted data uses, ownership, retention, deletion, audit rights, breach duties, portability and exit terms enforceable.
- Configure the service. Use agency-managed accounts, single sign-on and role-based access. Disable consumer sharing features, connect only approved repositories and enable logging, content filters and data-loss prevention where available.
- Test before production. Validate accuracy, security, privacy, accessibility, bias and failure behavior with representative but controlled data. Record the test method, results, limitations and acceptance criteria.
- Train and authorize users. Explain allowed and prohibited prompts, verification duties, records handling, incident reporting and how to recognize fabricated or unsafe output. Grant access only to users who complete the training.
- Monitor and reauthorize. Review logs, quality metrics, complaints, security events, model or terms changes and vendor reports. Reassess the use case when the model, data, workflow or legal environment changes.
Data protections to demand from the vendor
No secondary training without explicit consent
OMB says contracts should permanently prohibit vendors from using non-public agency inputs and outputs to further train publicly or commercially available AI algorithms unless the agency has explicitly consented. The prohibition should cover prompts, uploaded files, generated answers, feedback, system logs and any derived data that could reveal government information.
Clear ownership, access and retention
The contract should state who owns agency-provided data, outputs, fine-tuning material, evaluation sets and improvements. It should define where data is processed, how long it is retained, how deletion is verified, who can access it, how legal holds are handled and how the agency can export it. Government records may have retention schedules that conflict with a vendor’s default deletion setting, so records officials must be involved.
Security and incident response
Require documented encryption, identity and access controls, tenant isolation, vulnerability management, subcontractor disclosures, audit logs and a practical incident-notification deadline. Specify what assistance the vendor must provide for containment, forensics, public-records requests and reporting to oversight bodies. A security control is useful only if the agency can verify it through audits, attestations or test evidence.
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Agencies should retain enough rights to operate, test and monitor the system and to move data and workflows to another provider. Contracts should cover interoperable formats, export of prompts and outputs, model and configuration documentation, transition assistance and deletion after exit. A chatbot that cannot be replaced can turn a pilot into an uncontrolled dependency.
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How to compare two approved chatbot options
Price or model size should not be the first comparison. Evaluate each option against the agency’s actual mission and risk category.
| Evaluation area | Questions to answer |
|---|---|
| Authorization and accreditation | Is the service approved under the agency’s policy? Does the hosting environment have the government accreditation or authorization required for the data involved? |
| Data location and retention | Where are prompts and files processed? How long are they retained? Can the agency enforce deletion, legal holds and geographic restrictions? |
| Model-training use | Are agency inputs and outputs permanently excluded from shared-model training unless the agency gives explicit consent? |
| Privacy and records | Can the agency meet PII, privacy-impact, public-records and records-schedule obligations? Are SAOP and records officials able to obtain the necessary documentation? |
| Cybersecurity and incidents | Are identity controls, encryption, tenant isolation, audit logs, vulnerability management and incident-reporting duties documented and testable? |
| Ownership and licensing | Who owns data, outputs, evaluation material and improvements? Can the agency use them for oversight, testing and future operations? |
| Transparency and evaluation | Does the vendor provide capability and limitation statements, relevant training-data provenance, testing results, monitoring information and change notices? |
| Human control | Can users review, correct, override and document outputs before an official action? Are explanations and provenance available where the mission requires them? |
| Portability and exit | Can the agency export data, prompts, outputs, configurations and logs in usable formats and transition without unreasonable lock-in? |
| Mission performance | Has the agency tested the service on representative tasks, languages, documents and edge cases rather than relying on a generic benchmark? |
How employees should handle prompts and outputs
Before entering information
- Use only the agency-managed service and account approved for the task.
- Remove unnecessary names, identifiers, case numbers, secrets and other sensitive fields.
- Do not paste classified, law-enforcement-sensitive, procurement-sensitive or otherwise restricted content unless the specific environment is authorized for it.
- Check whether the prompt, file or resulting conversation is a government record and follow the applicable retention rule.
When reviewing an answer
- Verify quotations, dates, calculations, citations, legal conclusions and policy references against authoritative records.
- Assume the model can fabricate facts, omit exceptions or reproduce bias.
- Record the human reviewer, material edits and source documents when the output supports an official action.
- Never let an unverified answer make a rights-impacting or safety-critical decision.
When something goes wrong
- Stop using the affected workflow if the output creates an immediate safety, privacy, civil-rights or security risk.
- Preserve the relevant prompt, output, model version, user identity and timestamps under the agency’s incident and records procedures.
- Notify the designated security, privacy, program and acquisition contacts; do not conceal a problematic output by simply deleting the chat.
- Document corrective action, retesting and the decision to resume, restrict or discontinue the use case.
Common mistakes that make chatbot use noncompliant
“It is only a public summary”
Public source material can still be combined with non-public context in a prompt or reveal an agency’s internal work. Use an approved account and keep the input limited to what the task requires.
“The vendor says it is private”
Marketing language does not establish legal ownership, retention, deletion, training restrictions or incident duties. Those protections belong in enforceable terms and technical settings.
“A human looked at it, so the decision is safe”
Human review must be meaningful. The reviewer needs authority, time, training, source evidence and the ability to reject or override the output. A rubber stamp does not satisfy accountability for a high-impact use.
“A pilot does not need documentation”
OMB’s minimum practices include documentation, and an agency needs evidence to show what was tested, which data was used, who approved it and how problems were handled. Keep a decision record from the beginning.
Federal versus state and local agencies
The federal framework is not automatically a nationwide permission slip. State, local, tribal and territorial governments may be subject to different public-records laws, procurement requirements, constitutional constraints, privacy statutes, cybersecurity standards and sector rules. A city or state employee should consult that government’s counsel, privacy officer, security authority, records officer and procurement office before using a commercial chatbot, even if a federal agency has approved a similar tool.
Likewise, federal agencies must check their own current AI, privacy, security, procurement and records policies. OMB memoranda and agency directives can be amended or superseded, and a vendor’s service, model, subprocessors or terms can change after approval.
A practical decision rule
An agency can use a private AI chatbot for official work when it can answer “yes” to all of these questions:
- Is this exact service and use case authorized by the agency?
- Is the data classification compatible with the approved environment?
- Are privacy, security, records, civil-rights and procurement reviews complete?
- Does the contract prohibit unauthorized secondary use and preserve government rights?
- Are testing, monitoring, incident reporting and human-override procedures operating?
- Can the agency suspend the workflow and retrieve its data if the model or vendor changes?
If any answer is “no” or “unknown,” use a lower-risk alternative—such as public, synthetic or de-identified material—or pause until the gap is resolved. Availability is not authorization, and a chatbot’s fluent answer is not evidence that an official action is lawful or correct.
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