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Change the account boundary first. Put work prompts and files in a managed business workspace or API organization, verify whether the service can use content for model training, set a retention period with a deletion and legal-hold procedure, then repair identity permissions and sensitivity labels before enabling workplace copilots. Finally, limit integrations and sharing and turn on audit or compliance monitoring.
This order prevents the most expensive mistake: trying to solve a governance problem with a single “do not train” switch while consumer accounts, overbroad file permissions, long-lived chat history, or unmonitored integrations still expose company data.
1. Move business work out of personal AI accounts
The first setting is not a toggle inside a chatbot. It is the account type. Employees should use an organization-managed business workspace or an API organization for company work, not personal consumer accounts. A managed environment gives the business an administrative boundary for identity, access, retention, sharing and auditing.
In managed ChatGPT accounts, the administrator can control available services, exports, audits, retention, deletion and feature restrictions. OpenAI’s Help Center states: “Your administrator manages this account and the ChatGPT data associated with it.” That means an employee should not assume that a work conversation is private from the organization, nor that deleting a message personally removes every administrative or compliance copy.
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What to do
- Inventory every account type employees use for AI work, including personal accounts, team workspaces and API projects.
- Define which account types are approved for company data and prohibit business data in unmanaged accounts through policy and technical controls where available.
- Assign an owner for the approved workspace or API organization. Record who can administer users, exports, retention and integrations.
- Document what administrators may access and how employees are notified. This avoids a conflict between privacy expectations and the actual managed-account terms.
Do not treat a paid seat by itself as proof of enterprise controls. Verify the exact product edition, contract and administrator features in force for your organization.
2. Verify training-use settings before sending sensitive content
After the account boundary, verify whether business content is used to train or improve models. Do not infer the answer from a product name or a vendor’s consumer documentation; check the applicable business or API terms and the organization’s current setting.
| Environment | Documented position | What the administrator should verify |
|---|---|---|
| ChatGPT Enterprise and Business | OpenAI Academy says business customer content is not used to train models by default. | Confirm the exact edition, contract language and whether an explicit opt-in exists for the tenant. |
| OpenAI API | OpenAI says API data has not been used to train or improve models since March 1, 2023, unless the customer explicitly opts in. | Review organization-level and project-level data controls and any opt-in status. |
| Consumer or unmanaged accounts | The cited business assurances do not automatically apply. | Keep company data out unless your privacy and security review has approved that specific service and setting. |
The March 1, 2023 date is an API policy statement from OpenAI, not a universal rule for every product or account. Eligibility, contracts and settings can change, so retain a dated record of what you verified.
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Approved API organizations can select Zero Data Retention or Modified Abuse Monitoring. Project settings may inherit organization controls or override them, depending on the configuration. Review both levels: an organization-wide choice can be undermined by a project-specific exception, while a restrictive project may not cover other projects created later.
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Make the decision auditable
Record the approved training-use posture, the person who verified it, the product tier, the contract or policy version and the date of review. Recheck after a contract amendment, a new model endpoint, a workspace migration or a major product change.
3. Set retention deliberately, with deletion and legal holds
“Not used for training” does not mean “deleted immediately.” A business needs a retention period for prompts, outputs, attachments, logs and administrative records, together with a repeatable deletion workflow.
OpenAI Academy reports that Enterprise owners can set custom retention with a 90-day minimum (guidance updated in 2026). OpenAI’s enterprise privacy information says deleted conversations are removed within 30 days, and its retention guidance similarly says permanent deletion is scheduled within 30 days. Those schedules remain subject to security or legal exceptions, including circumstances in which data must be preserved.
| Retention question | Decision to document |
|---|---|
| How long are ordinary conversations kept? | Choose the shortest period that supports operational, regulatory and investigative needs. Enterprise custom retention has a documented 90-day minimum in the cited guidance. |
| What happens when a user deletes a chat? | Define the deletion request path and explain that permanent deletion is scheduled within 30 days under the cited OpenAI policy, unless an exception applies. |
| What is placed on legal hold? | Name the legal or compliance owner, the trigger, the preserved data types and the release process. |
| Which records are outside chat history? | Include API logs, exports, abuse-monitoring records, audit events and connected-system copies where applicable. |
| Does shorter retention have a cost? | Yes. OpenAI warns that shorter periods may compromise product experience, including the continuity provided by conversation history. |
A practical retention workflow
- Classify AI records by business purpose: transient assistance, operational work product, regulated record or investigation material.
- Assign a default period to each class and identify the law, contract or internal schedule supporting it.
- Configure the workspace or API controls to match the approved default. If the platform cannot express the policy precisely, document the compensating control.
- Test deletion with a non-sensitive account. Confirm what disappears, what remains temporarily and what is retained for security or legal reasons.
- Write a legal-hold procedure that overrides routine deletion and names who can release the hold.
There is no universal “correct” number of days for employee AI chats. The defensible choice is the minimum period that meets your documented obligations while preserving the functionality users genuinely need.
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4. Repair identity permissions and sensitivity labels before enabling a workplace copilot
A workplace copilot can retrieve information that the signed-in user is already allowed to access. The critical risk is therefore often the underlying permission model, not an AI model bypassing it.
Microsoft states that Copilot “respects your identity model and permissions, inherits your sensitivity labels, applies your retention policies, supports audit of interactions, and follows your administrative settings.” In practice, a user with excessive access to a SharePoint site, mailbox or file can receive AI-assisted answers drawn from that overbroad access. Copilot does not make an incorrectly open document private.
Pre-launch permission review
- Find groups, shared links and sites that grant access more broadly than the job requires.
- Remove stale accounts, inherited permissions and anonymous or organization-wide links that are no longer justified.
- Check whether sensitive labels are consistently applied to documents, messages and sites.
- Test representative users: an ordinary employee, a manager, a contractor and an administrator should each see only the information their role permits.
- Verify that retention and audit policies apply to the Copilot interactions and source content your compliance team considers in scope.
Ask “Can Copilot see everything in SharePoint?” The accurate answer is no, not by default: it follows the tenant’s identity and permissions. But if the tenant grants everyone access to a repository, Copilot can use that accessible content in responses. Fix the repository permissions before broad rollout.
5. Restrict integrations, sharing and custom assistants
Every connector, plug-in, custom assistant or export path creates another route by which prompts or retrieved data can leave the core workspace. OpenAI governance guidance recommends deciding which features and third-party integrations are enabled, controlling the sharing scope of custom GPTs and considering Compliance API or SIEM/DLP integrations.
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Start with an allow-list
- List each enabled integration and the data it can read or write.
- Disable features with no approved business owner or documented use case.
- Limit custom-GPT sharing to the smallest group that needs it; do not default to public or organization-wide publication.
- Review whether an integration stores copies, sends data to another processor or permits user-controlled exports.
- Require a security and privacy review before enabling a new connector, model or action.
Monitoring should cover administrative changes, sharing changes, high-risk prompts or data transfers and deletion events. Where available, route compliance events to the organization’s existing SIEM or DLP process rather than creating an isolated AI log that nobody reviews.
6. Use this comparison checklist when selecting or renewing a service
Procurement and security teams should compare services on the controls that determine exposure, not only on model quality or seat price.
| Dimension | Questions to ask |
|---|---|
| Retention duration | Can the organization set a custom period? Is there a minimum? Does it cover chats, files, logs and API data separately? |
| Legal holds | Can routine deletion be suspended for a defined matter, and who can authorize or release the hold? |
| Training-use default | Is business content excluded by default, and can a customer or project opt in accidentally? |
| Administrator visibility | Can administrators audit, export, restrict, retain or delete data, and are employees told about that access? |
| Identity and labels | Does the service inherit tenant permissions and sensitivity labels, and are those controls tested before launch? |
| Integration scope | Which connectors, custom assistants, actions and exports are available, and can administrators disable them? |
| Audit capability | Are interaction and configuration events available for compliance, SIEM or DLP workflows? |
| Data residency | Where are prompts, outputs, attachments and logs stored or processed for the specific edition and region? |
| Conversation-history impact | What user features stop working or become less useful when retention is shortened? |
Ask vendors to answer for the exact edition, region and contract you will deploy. A broad marketing statement is not a substitute for a tenant-level setting or a signed term.
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- Freeze unmanaged use for sensitive work. Tell employees which account types are approved and move active projects into the managed workspace or API organization.
- Verify training use. Capture the current default, any opt-in, the applicable contract and the date of verification.
- Set retention and deletion. Choose a documented period, configure it, test deletion and publish the legal-hold exception.
- Audit identity and labels. Correct overbroad SharePoint, Exchange and workspace permissions before enabling retrieval across business repositories.
- Reduce the integration surface. Disable unapproved connectors, constrain custom-assistant sharing and review export paths.
- Enable monitoring. Connect available audit, Compliance API, SIEM or DLP feeds to an owner who can investigate and respond.
- Recheck after change. Repeat the review after a product update, model addition, contract change, migration or new data source.
Common mistakes and their fixes
“We turned off training, so we are safe.”
Training exclusion does not correct an employee using a personal account, an over-permissioned file repository or an unrestricted connector. Apply the account, retention, permission and integration controls as a set.
“Delete means gone immediately.”
Deletion may be scheduled rather than instantaneous. Explain the 30-day deletion schedule cited for OpenAI enterprise data and document security or legal exceptions.
“Shorter retention is always better.”
Shorter retention reduces the time data remains available, but it can remove conversation context and weaken product usability. Set the shortest period that still supports the business purpose and legal requirements.
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The cited Microsoft guidance says Copilot follows identity, permissions, labels, retention and administrative settings. If a response exposes too much, investigate the user’s underlying access and the source item’s labels first.
“One organization setting covers every API project.”
Project-level controls can inherit or override organization settings. Review each project and prevent new projects from silently using a weaker posture.
Conclusion: change controls in this order
Businesses should first establish a managed account boundary, then verify and document training-use defaults, set retention with deletion and legal-hold rules, repair identity permissions and sensitivity labels, and finally restrict integrations while monitoring use. ChatGPT Enterprise and Business are described as not using business content for training by default; the API policy cited by OpenAI excludes training use since March 1, 2023 unless a customer opts in. Those statements still require confirmation for the exact tier and contract. Enterprise custom retention has a documented 90-day minimum, while deleted conversations are scheduled for removal within 30 days subject to exceptions. Revisit every control when the product, contract, region or connected data changes.
Quick Recap
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