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1. Inventory and approve the AI services employees can use
Start with an inventory of the AI services and features employees can reach—not just standalone chatbots. Include AI built into productivity suites, agents, connectors, APIs, and other integrations. Record which employee groups may use each service and for what work.
Require employees to use company-authorized services under managed work accounts. Consumer accounts and business workspaces can have different data terms and administrative controls, so do not treat a familiar product name as proof that an account is covered by workplace protections. A blocklist alone is not a complete control: unmanaged apps and shadow agents may remain accessible, making ongoing discovery and review necessary.
Decide what is approved
- Record the product, account type, plan or edition, intended users, connected data sources, and business purpose.
- Identify who approves new services and integrations, and how employees request access.
- Revisit the inventory when the organization adds a service, enables an embedded AI feature, or changes its licensing or configuration.
2. Require managed identities and grant access by role
Use central identity controls where available, and grant access only to employees who need the service for their role. Plan for joiners, role changes, and departures: access should be added, adjusted, or removed through the organization’s normal identity lifecycle rather than left to individual accounts.
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Capabilities vary by product and plan. OpenAI lists SSO and workspace roles for ChatGPT Business, and additional SCIM and role-based access controls for Enterprise and Edu. Google Workspace administrators can control Gemini access and apply settings to organizational units or configuration groups. Check current entitlements for the precise product and contract before relying on a feature.
Use the controls the selected service actually provides
- Confirm whether the service supports SSO, MFA, administrative roles, and automated provisioning or deprovisioning.
- Scope access to appropriate teams, organizational units, or groups where supported.
- Test the access-removal process with a test account or approved change procedure before relying on it operationally.
3. Fix source-data permissions before enabling AI retrieval
Review permissions in the systems that hold company content before connecting them to AI. Check shared drives and sites, file links, groups, inherited access, and service accounts. Remove unnecessary access at the source rather than expecting an AI prompt or assistant to enforce repository permissions.
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Microsoft says Copilot follows existing permissions and warns that overshared or poorly governed content can affect responses and increase risk. Microsoft describes the behavior this way: “Copilot only accesses data that users are authorized to access.” That describes Microsoft’s product behavior; it does not mean every underlying permission is appropriate. Google says Gemini’s Workspace data access follows the signed-in user’s access rights, while some file-owner restrictions can further limit Gemini’s access even when a file is shared.
Permission review checklist
- Find broadly accessible or externally shared files, folders, sites, and groups.
- Check whether inherited permissions, stale groups, or service accounts expose more content than intended.
- Verify access using representative employee accounts, especially accounts with different roles and group memberships.
- Correct the source permissions, then confirm that the intended users can still retrieve the content they need.
4. Verify the data terms for each service and account
For every approved service, establish whether employees use a consumer account, managed work account, API, or enterprise workspace. Review the terms and data-protection agreement that apply to that exact arrangement. Confirm how prompts, uploads, and connected source data are handled, whether they are used for model training, who processes them, and what retention and deletion arrangements apply.
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Do not transfer a protection claim from one product or account type to another. Microsoft says organizational Copilot use is covered by Microsoft Product Terms and the Data Protection Addendum, with Microsoft acting as processor; Microsoft also says Copilot prompts, responses, and accessed Graph data are not used to train foundation models. OpenAI describes business access controls, a DPA, and data-residency options. Google distinguishes qualifying Gemini use as a Workspace core service, which receives enterprise data protections, from Gemini use as an additional service subject to different terms and handling. These are vendor statements about their own products, not independent testing.
Record the arrangement
- Product, plan, account type, region, and governing terms or DPA.
- Whether prompts, uploads, and connected data may be used for model training.
- Applicable retention, deletion, and data-residency options.
- Any conditions or exclusions tied to a particular feature, license, or configuration.
5. Review connectors, apps, agents, and actions
Treat each connection as a separate access decision. Record what data it can reach, what permissions it receives, whether it can only read or can also write or take other actions, which provider receives the data, and what activity is logged. Disable integrations that are not needed and choose the narrowest available permission scopes.
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OpenAI says information sent to non-synced third-party apps is subject to the third party’s own terms. It also says app-log and compliance API availability varies by product, app, and workspace configuration, and that safeguards reduce—but do not eliminate—prompt-injection and unauthorized-access risks. Do not assume a business administrator can inspect ordinary private conversations: OpenAI says Business administrators do not automatically receive that access.
Review each connection before enabling it
- Identify the data requested and the provider that receives it.
- Confirm whether access is read-only or permits changes, messages, or other actions.
- Check the third party’s terms and the actual activity and compliance records available for that app.
- Disable unused apps and revoke permissions when a connection is no longer needed.
6. Set retention, DLP, audit, and incident expectations
Choose controls based on the service’s real capabilities and the organization’s requirements. Where supported, use data loss prevention (DLP), sensitivity labels, retention policies, audit events, and security dashboards. Test the records and export paths available to administrators before promising that they satisfy an audit, investigation, or legal requirement.
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Microsoft documents DLP, governance dashboards, sensitivity-label inheritance, retention policies, and audit of interactions for Copilot, while warning that policy support varies by subscription. Google documents an administrator setting for Gemini conversation history and retention choices; the available settings and defaults can change, so verify the current Google Workspace Admin Help guidance for the edition and configuration in use. OpenAI cautions that app activity and compliance logging coverage varies by app and configuration.
Make the controls operational
- Define which records the organization must retain, for how long, and who can access them.
- Test what is captured for representative AI interactions and connected-app activity, and verify how records can be exported.
- Document what the service does not log or expose to administrators; do not promise universal conversation visibility.
- Set an incident route for accidental disclosure, suspicious connector behavior, or inappropriate access, and assign responsibility for response.
- Schedule periodic reviews of policies, permissions, licenses, integrations, and actual logging coverage.
7. Give employees clear rules and training
Tell employees which service and account to use, what types of information may be entered, and how to handle customer, employee, regulated, confidential, or privileged data. Explain how to report an accidental disclosure and require employees to check AI output before relying on it. Microsoft’s workplace guidance advises using company-authorized services, handling inputs cautiously, avoiding sensitive or confidential information, and double-checking output; adapt those principles to the organization’s policy and actual controls.
Make the rules specific
- Name the approved services and explain that personal or consumer accounts are not substitutes for managed work accounts.
- Classify data as allowed, restricted, or prohibited for each approved use case.
- Explain which connected apps or AI actions are approved and how employees request a new one.
- Give employees a simple reporting path for accidental disclosures or unexpected AI access.
- State that AI-generated answers may be inaccurate and identify any required human review.
How to compare workplace AI controls
When choosing between services, compare the controls available under the actual plan and configuration—not the product names alone. Prefer a service that fits the identity and productivity systems already in use when it meets the organization’s requirements, but verify each control rather than assuming integration guarantees coverage.
Quick Recap
| Decision area | What to verify |
|---|---|
| Identity and roles | SSO, MFA, automated provisioning and deprovisioning, group or organizational-unit scoping, and administrative roles. |
| Data boundaries | Which source systems and files the AI can access, whether repository permissions are inherited, and how oversharing is discovered and corrected. |
| Data-use terms | Training use, provider role, DPA coverage, third-party app terms, account-type distinctions, and regional options. |
| Governance | DLP, sensitivity labels, retention, audit events, export coverage, data residency, and incident response. |
| Operational fit | Existing identity and productivity stack, license availability, user experience, administrator workload, and how unmanaged use will be found. |
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
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