--- 格式版本: 2 标题: "ChatGPT Work admin FAQ | ChatGPT Learn" 原文链接: "https://developers.openai.com/codex/enterprise/work-admin-faq" 发布日期: "2026-08-16" 发布时间校准状态: "found" 发布时间需复核: "否" 发布时间来源: "rule:local:strict_original_body" 发布时间证据: "Published Time: Sun, 16 Aug 2026 16:09:35 GMT" 发布时间校准原因: "规则确认唯一严格发布时间，来源 local:strict_original_body" 发布时间校准置信度: "high" 发布时间候选数量: 4 发布时间严格候选数量: 1 发布时间原页读取状态: "source template page reused from URL open" 发布时间未找到原因: "" 发布时间校准时间: "2026-08-17T00:09:41+08:00" 发布时间仲裁状态: "skipped" 发布时间仲裁尝试次数: 0 发布时间仲裁耗时毫秒: 0 发现时间: "2026-08-16T23:54:06+08:00" 入库时间: "2026-08-16T16:09:41.828Z" 来源平台: "固定入口" 搜索渠道: "fixed_url" 搜索词: "https://developers.openai.com/blog" 匹配关键词: - "deployment" - "performance" - "latency" - "throughput" - "AI" 相关厂家: - "OpenAI" - "Microsoft" - "AWS" - "Google" - "Oracle" 相关专家: [] 内容类型: "网页" 抓取工具: "Jina Reader" 清洗工具: "Jina Reader Markdown + Defuddle/Readability 正文提取" 原始附件: [] AI优质: "否" AI打分: 10 AI分档: "非优质" AI质检状态: "不通过" AI打分理由: "资料为ChatGPT Work管理员FAQ，完全未涉及超节点、AI Rack、机柜级AI基础设施、硬件架构、互连、供电、散热或量产落地等主题，与项目关注范围无关。" AI质检模型: "ali-deepseek-v4-flash" AI质检时间: "2026-08-17T00:09:52+08:00" AI主题相关性: 0 AI来源权威性: 5 AI新颖性: 0 AI技术细节: 0 AI商业部署信号: 0 AI完整性: 5 AI摘要: "该页面是OpenAI开发者文档中ChatGPT Work管理员FAQ的入口，但正文仅包含站内导航与文档索引，没有提供具体的FAQ问答内容。" AI摘要模型: "ali-deepseek-v4-flash" AI摘要时间: "2026-09-07T03:26:40.002Z" 采集批次: "2026年8月16日20点37分10秒" 采集批次ID: "20260816-203710-016" 去重键: "https://developers.openai.com/codex/enterprise/work-admin-faq" --- Title: ChatGPT Work admin FAQ | ChatGPT Learn URL Source: https://developers.openai.com/codex/enterprise/work-admin-faq Published Time: Sun, 16 Aug 2026 16:09:35 GMT Markdown Content: For the complete documentation index, see [llms.txt](https://developers.openai.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to the page URL. 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### Identity and authentication * [Authentication overview](https://developers.openai.com/codex/auth) * [Personal Access Tokens](https://developers.openai.com/codex/enterprise/access-tokens) * [Service accounts](https://developers.openai.com/codex/enterprise/service-accounts) ### Workspace access, policy, and models * [Groups and provisioning](https://developers.openai.com/codex/enterprise/groups-and-provisioning) * [Roles and workspace permissions](https://developers.openai.com/codex/enterprise/roles-and-workspace-permissions) * [GPTs and Sharing](https://developers.openai.com/codex/enterprise/gpts-and-sharing) * [Managed configuration](https://developers.openai.com/codex/enterprise/managed-configuration) * [Prisma AIRS](https://developers.openai.com/codex/enterprise/prisma-airs) * [HIPAA configuration](https://developers.openai.com/codex/hipaa-configuration) * [Workspace model availability](https://developers.openai.com/codex/enterprise/workspace-model-availability) ### Plugin and connector controls * [Plugin controls](https://developers.openai.com/codex/enterprise/apps-and-connectors) * [Skill controls](https://developers.openai.com/codex/enterprise/skills) ### Usage, governance, and compliance * [Governance](https://developers.openai.com/codex/enterprise/governance) * [Workspace analytics](https://developers.openai.com/codex/enterprise/workspace-analytics) * [Analytics API](https://developers.openai.com/codex/enterprise/analytics-api) * [Compliance API and audit events](https://developers.openai.com/codex/enterprise/compliance-api) ### Deployment and model providers * [Manage app updates](https://developers.openai.com/codex/enterprise/manage-app-updates) * [Windows app deployment](https://developers.openai.com/codex/enterprise/windows-deployment) * [Remote connections](https://developers.openai.com/codex/remote-connections) * [Amazon Bedrock](https://developers.openai.com/codex/amazon-bedrock) Copy Page # ChatGPT Work admin FAQ Manage access, data, governance, observability, usage, and incident controls for ChatGPT Work Copy Page ChatGPT Work brings the technology behind Codex into ChatGPT for longer, multi-step tasks. It can gather context from chats, files, workspace resources, and connected systems; use approved tools; and create review-ready outputs. Access, context, actions, network behavior, and credit use vary by plan, workspace settings, source permissions, and surface. ## Overview ChatGPT Work lets users delegate longer, multi-step tasks to ChatGPT. It can gather information from connected sources, reason across steps, create documents, presentations, or analyses, and return results for review. ChatGPT Work is available on supported web, mobile, and desktop surfaces for eligible plans and workspaces. Where supported, workspace owners or authorized admins can manage Work Cloud, Work Local, and Codex Local through distinct permissions. For eligible Enterprise and Edu workspaces, the default workspace role includes Work unless an authorized administrator turns it off. Browser and network controls further restrict Work Cloud, and availability depends on role, plan, workspace, and region. See [ChatGPT Work and Codex](https://help.openai.com/en/articles/20001275-chatgpt-work-and-codex). This FAQ explains how admins manage ChatGPT Work: access and data controls, compliance and visibility, usage and spend, incident response, and rollout practices. For the hosted execution model and security boundaries, see [ChatGPT Work Overview](https://developers.openai.com/codex/enterprise/chatgpt-work-overview). ## Core administrative controls Administrators govern ChatGPT Work through these control layers: * **Access to the enterprise workspace:** Identity and access controls manage authentication and access to the workspace. Depending on the plan and configuration, administrator-controlled identity features can include SSO, domain verification, SCIM provisioning, user lifecycle management, and identity-group synchronization. SCIM and synchronized identity groups aren’t included with ChatGPT Business. Users can enable account-level OpenAI MFA. ChatGPT doesn’t provide workspace-wide MFA enforcement; organizations that require it should enforce SSO and MFA through their identity provider. Manage SSO and related identity settings in the [Global Admin Console](https://help.openai.com/en/articles/12289294-admin-portal). See [Multi-factor authentication](https://help.openai.com/en/articles/7967234-enabling-or-disabling-multi-factor-authentication-mfa). * **Access to ChatGPT Work within the workspace:** Where available, Work Cloud governs hosted Work across supported web, mobile, and desktop surfaces. Work Local governs local desktop Work, while Codex Local controls supported local Codex access in desktop, CLI, and IDE clients. Cloud browser and network settings further restrict Work Cloud. Custom role-based access control (RBAC) and available permissions depend on the plan and workspace. * **Group membership:** On plans that support SCIM, synchronize groups through an identity provider so access updates as employees join the organization, change roles, or leave. See [Groups and provisioning](https://developers.openai.com/codex/enterprise/groups-and-provisioning). * **Workspace and member roles:** Built-in Enterprise roles include Owner, Admin, Member, and Analytics Viewer. On supported plans, custom roles and member RBAC control access to ChatGPT Work, plugins, and other capabilities. Where seat types apply, members also need a seat that includes ChatGPT; a Codex-only seat doesn’t grant access to Work. See [Roles and workspace permissions](https://developers.openai.com/codex/enterprise/roles-and-workspace-permissions). * **Plugins and apps:** Plugin policy governs plugin availability and installation. App access, action controls, and approval behavior are configured separately. Workspace Agents have their own controls where available. See [Plugin controls](https://developers.openai.com/codex/enterprise/apps-and-connectors), [Plugins](https://developers.openai.com/codex/plugins), and the [App security white paper](https://cdn.openai.com/business-guides-and-resources/app-security-whitepaper.pdf). * **Source-system permissions:** A user can access only the content and actions allowed by the account or shared connection in the native application. See [Admin controls, security, and compliance in apps](https://help.openai.com/en/articles/11509118-admin-controls-security-and-compliance-in-apps-enterprise-edu-and-business). * **Approval and action restrictions:** For apps that support Action control, admins can allow all actions, read-only actions, or a custom set and decide how newly added actions are handled. App permissions separately determine when ChatGPT asks before using an app. * **Credits:** ChatGPT Work and Codex share pricing, credits, and usage limits. Eligible Enterprise and Edu admins can set monthly per-user limits through a workspace default, group defaults, and individual overrides. Users can request increases when the workspace allows it. Business follows a separate credit and spend-control model. See [ChatGPT usage limits and spend controls](https://developers.openai.com/codex/enterprise/usage-limits). * **Analytics and reporting:** The Global Admin Console and workspace analytics support adoption and credit-usage analysis. Use the Compliance API and Codex reporting surfaces for their documented event and product scopes; review the current schemas before promising coverage of particular prompts, files, approvals, actions, errors, or tool calls. See [Governance](https://developers.openai.com/codex/enterprise/governance). ## Access, data, systems, and user actions ### How are access to data, systems, and user actions protected? ChatGPT Work is governed by the identity, access, and permission controls already established in your ChatGPT workspace. Administrators use identity management, workspace roles, and, on eligible plans, [RBAC](https://help.openai.com/en/articles/11750701-rbac) to determine who can use ChatGPT Work. Where supported, access can be synchronized with your identity provider through [SCIM](https://help.openai.com/en/articles/10011769-openai-platform-scim-integration-faq) and group synchronization. This lets you manage access and permissions centrally as employees join the organization, change roles, or leave. Underlying source systems enforce the permissions of the account or approved shared connection used for the operation. An individual connection uses that person’s source-system access. An agent-owned or shared connection can give authorized agent users access through the connected account, including data or actions their own account couldn’t access. Restrict the connection’s scopes, available actions, and agent audience to the intended business need. See [Workspace Agent connections and permissions](https://help.openai.com/en/articles/20001143-chatgpt-workspace-agents-for-enterprise-and-business). [](https://developers.openai.com/codex/enterprise/work-admin-faq)[](https://developers.openai.com/codex/enterprise/work-admin-faq) ### How does ChatGPT Work access data and context? ChatGPT Work can use the current chat, uploaded files, workspace resources, and connected systems through approved apps and, when applicable, plugins. Depending on enabled capabilities and permissions, this can include documents, repositories, tickets, channels, email, and calendars. Earlier files can be available through the current chat, supported projects, authorized Library access, or enabled automatic Library references. Saved memories follow their own workspace and user controls. Each context source keeps its own controls: users supply chat context, admins manage workspace resources, and connected systems enforce authentication and permissions. ChatGPT Work can access only information authorized for the user or an approved shared connection. ChatGPT Work inherits applicable ChatGPT workspace protections. Residency, retention, logging, and feature availability vary by plan, region, surface, and connected system, so confirm coverage for your configuration. ### What high-impact actions are restricted or require review? Action risk varies. Reading or drafting is generally lower impact than changing data, sharing information, or acting in external systems. Combine roles, narrow permissions and credentials, and supported approvals to limit higher-impact actions to trusted, reviewed use. Common action categories include: * **Read:** Access, search, or summarize information from approved sources without changing the underlying data. * **Draft:** Prepare documents, email, reports, code, or other content for a person to review before use. * **Write:** Create, update, or delete records in connected systems, such as documents, tickets, repositories, or project-management tools. * **Share:** Send, publish, or otherwise make information available to more people, systems, or external destinations. * **Schedule:** Start a task at a future time or on a recurring schedule without requiring a user to start each run. * **Execute:** Run code, shell commands, browser automation, or other tool-driven tasks that interact directly with external environments. For higher-impact actions, use human review, restricted credentials, narrow scopes, and supported approvals. Plugin actions still follow each integration’s permissions and security controls. ## Compliance [](https://developers.openai.com/codex/enterprise/work-admin-faq)[](https://developers.openai.com/codex/enterprise/work-admin-faq) ### How does ChatGPT Work support enterprise privacy and data commitments? ChatGPT Work uses the privacy, security, and data commitments applicable to the customer’s ChatGPT workspace, subject to plan, configuration, surface, feature, and region. For ChatGPT Enterprise, this includes [no training on business data by default](https://help.openai.com/en/articles/8983130-what-if-i-want-to-keep-my-history-on-but-disable-model-training), encryption in transit and at rest, workspace-level access controls, and supported audit logging. Coverage for data residency, inference residency, HIPAA, or a Business Associate Agreement isn’t universal. Confirm current [data and inference residency guidance](https://help.openai.com/en/articles/9903489-data-residency-and-inference-residency-for-chatgpt) and the customer’s agreement for the features and regions in use. Connected services have their own retention, logging, access, residency, and compliance requirements. When ChatGPT Work uses plugins, repositories, or third-party systems, evaluate both the ChatGPT workspace controls and the connected system’s controls. For Codex activity, enterprise controls can extend to development environments, repositories, configured tools, and related activity. Review [Admin rollout guide](https://developers.openai.com/codex/enterprise/admin-setup) and [Governance](https://developers.openai.com/codex/enterprise/governance) alongside the workspace controls. ### What data is stored, retained, or deleted? Data retention and deletion for ChatGPT Work are governed by the ChatGPT workspace plan, administrative settings, and the capabilities in use. Retention can vary across the information ChatGPT Work accesses. Conversations and eligible Library files follow their applicable workspace settings. Project files, transient uploads, saved memories, compliance events, synchronized app data, and third-party records can have separate retention and deletion rules. See [Chat and file retention policies](https://help.openai.com/en/articles/8983778-chat-and-file-retention-policies-in-chatgpt). ChatGPT Work can create chat content, uploaded or generated files, artifacts, and execution metadata. Codex chats can also create repository or environment metadata, command output, diffs, and logs. Check the current product and [Compliance API](https://developers.openai.com/codex/enterprise/compliance-api) documentation for exact data classes, retention periods, and deletion paths. Review retention requirements across both the ChatGPT workspace and connected enterprise systems so your organization’s data governance, compliance, and record-retention policies apply to each system. ## Observability ### What usage data is available to admins or owners? Admins and owners can use product analytics and compliance logs for different kinds of visibility. The Global Admin Console provides supported ChatGPT and Codex adoption and credit-usage views; available user, product, agent, and model breakdowns depend on the analytics surface and workspace. For eligible workspaces, the Compliance API provides covered ChatGPT conversation records, including supported cloud Work activity. Coverage depends on the product, surface, permissions, available endpoint, and documented event schema. See [Workspace analytics](https://developers.openai.com/codex/enterprise/workspace-analytics) and the [Compliance API](https://developers.openai.com/codex/enterprise/compliance-api). ### Are prompts, outputs, files, actions, or tool calls logged? For eligible Enterprise and Edu workspaces, the Compliance Logs Platform provides Work user prompts and agent responses. [Connected app calls are separately logged](https://help.openai.com/en/articles/11509118-admin-controls-security-and-compliance-in-apps-enterprise-edu-and-business), and eligible workspaces can access active Library files through supported [Library-specific Compliance API endpoints](https://help.openai.com/en/articles/20001052-library-for-chatgpt). These records don’t establish a complete audit trail for every hosted file operation, shell command, browser interaction, tool invocation, or approval. Confirm the current event and product coverage in the authenticated Compliance API documentation. The Compliance Logs Platform retains data for 30 days. Export records continuously to an approved electronic discovery, data loss prevention, SIEM, or data-lake system when your organization requires longer retention. See the [OpenAI Compliance Platform guide](https://help.openai.com/en/articles/9261474-compliance-api-for-chatgpt-enterprise-edu-and-chatgpt-for-teachers). ### Can unusual behavior, failures, or usage spikes be detected quickly? Workspace analytics, compliance logs, and connected monitoring tools help admins review usage and investigate supported ChatGPT, Work, and Codex activity. Depending on the selected reporting surface, signals can include active users, supported messages, app activity, agent usage, authentication or administrative events, and credit consumption. Exported logs can support electronic discovery, data loss prevention, SIEM, auditing, and investigations. Detection quality depends on plan, event coverage, attribution, freshness, and configured rules. Signals that can warrant review include unexpected increases in usage or credit consumption, unusual user or agent activity, recurring operational errors, and relevant authentication or administrative events. Confirm the exact signals against the applicable analytics, compliance, and audit-log schemas. For Codex activity, Codex analytics and the Analytics API provide supported adoption and activity metrics. Organizations using local Codex clients can opt in to OpenTelemetry exports for events such as API requests, errors, prompt metadata, tool-approval decisions, and tool results. Prompt contents are redacted unless `otel.log_user_prompt = true` is enabled as a separate explicit opt-in. See [Monitoring and telemetry](https://developers.openai.com/codex/agent-approvals-security#monitoring-and-telemetry). This local Codex telemetry doesn’t provide an OpenTelemetry export for ChatGPT Work on the web. ## Governance ### How can admins control access, permissions, and policies? Governance spans three related but separate layers: * **ChatGPT Work access controls** determine who can use ChatGPT Work on each surface. * **Workspace Agent controls** determine who can build, publish, share, schedule, or configure reusable agents and shared connections, where Workspace Agents are available. * **Codex managed configuration** governs covered local Codex runtime behavior and doesn’t configure hosted ChatGPT Work. Managed configuration constrains supported runtime behavior. It doesn’t grant workspace access, replace RBAC, or revoke a user’s workspace access. These layers aren’t one uniform ChatGPT Work policy surface. Analytics and compliance logs provide additional visibility within their documented product and event scopes. For supported local Codex clients, enterprise administrators can apply [managed configuration](https://developers.openai.com/codex/enterprise/managed-configuration) and [permission profiles](https://developers.openai.com/codex/permissions). Those local-client controls don’t grant access to, or replace the workspace permissions for, hosted ChatGPT Work. ### Can access be scoped by group, role, workspace, or capability? Yes. On eligible Enterprise and Edu plans that support custom member RBAC, ChatGPT Work capabilities can be scoped with workspace roles, identity groups, and administrator-defined permissions. ChatGPT Business uses applicable workspace-level controls but doesn’t include custom member RBAC or SCIM group synchronization. Assign supported capabilities based on business need and organizational policy. See the [RBAC guide](https://help.openai.com/en/articles/11750701-rbac) and this [RBAC walkthrough](https://vimeo.com/1207482321/d1286e4467?share=copy&fl=sv&fe=ci). Where custom RBAC is available, organizations can use it to determine which users can access ChatGPT Work, manage workspace settings, configure approved plugins, or use supported Workspace Agent features. For eligible Enterprise and Edu workspaces, monthly usage limits can support a phased rollout through a workspace default, group defaults, and user overrides. Access to connected systems remains independently governed. Scope plugins, shared credentials, repositories, and write-capable actions to the minimum required audience using workspace permissions, plugin settings, and the source system’s controls. For supported local Codex clients, managed configuration can further restrict local runtime capabilities. Hosted Work follows its own workspace and product-specific controls. ### How are runtime and network boundaries governed? The security boundaries for ChatGPT Work depend on the task. A standard Chat conversation, a connected workflow, a scheduled task, and a Codex chat can run in different environments with different permissions, tools, and network access. Govern each execution environment through its applicable controls. Work Cloud governs hosted Work across supported web, mobile, and desktop surfaces. Work Local governs local desktop Work, and Codex Local controls supported local Codex access in desktop, CLI, and IDE clients. Browser and shell network permissions further restrict Work Cloud. Search, apps, plugins, available Workspace Agents, and source-system permissions remain separate controls. Applicable managed configuration and local runtime policies govern only their supported local experiences. These controls aren’t interchangeable. For Codex activity, local runs in the ChatGPT desktop app, CLI, and IDE execute on the user’s machine with operating-system sandboxing and approval policies. Codex cloud runs chats in isolated OpenAI-managed environments. For supported local clients, enterprise administrators can use managed requirements to constrain permission profiles, approvals, filesystem and network access, MCP servers, hooks, command rules, and other supported runtime behavior. ## Usage and cost [](https://developers.openai.com/codex/enterprise/work-admin-faq)[](https://developers.openai.com/codex/enterprise/work-admin-faq) ### How does ChatGPT Work usage translate into spend over time? [ChatGPT Work and Codex share pricing, credits, and usage limits](https://developers.openai.com/codex/pricing). Consumption varies with the model and capability, context size, task duration, tool use, and output size. Standard Chat usage is separate. The highest-variance patterns are often workflows that run frequently, retrieve or process large amounts of information, call multiple tools or apps, retry after failures, or produce large artifacts. Cost-sensitive examples include scheduled or recurring work, large files, broad retrieval across enterprise sources, repeated app calls, and Codex chats that process repositories, run commands, or use cloud environments. Workspace Agent API triggers can also add usage where available. Use spend controls, usage analytics, and reporting to monitor these patterns over time. Review usage by the dimensions supported in the current analytics surface and adjust limits or rollout scope based on business value. Don’t treat aggregated analytics as exact per-workflow cost attribution. Workspace analytics, compliance logs, and connected monitoring tools can help administrators review usage and investigate supported activity. The ability to detect risky or unusual behavior depends on plan, log coverage, attribution, data freshness, and the rules configured in your monitoring systems. ### What usage limits, alerts, or caps are available? Eligible Enterprise and Edu workspaces can use monthly per-user limits and workspace-wide spend controls for credit-based usage: * **Monitor credit consumption:** Review supported credit-usage reports in the Global Admin Console and workspace settings. * **Set a default monthly limit:** Establish a default per-user credit limit for the workspace. * **Apply group-specific limits:** Give groups monthly per-user defaults that reflect their workflows, responsibilities, or rollout stage. * **Create user overrides:** Give a specific user a different limit without changing the default for the entire group. * **Review increase requests:** If requests are enabled, users can request a higher monthly limit. Approval creates a user override. * **Control overall workspace exposure:** Configure workspace credit alerts and the overage limit separately in the Global Admin Console. Alerts notify recipients; the overage limit controls eligible usage after the committed credit pool is exhausted. * **Export usage data:** Eligible Enterprise administrators can access credit-usage data through the unified Cost API for internal reporting or monitoring. Users can view their own usage and, if enabled, request more credits, but they can’t change assigned limits. See [Manage usage limits and overages](https://help.openai.com/en/articles/20001001-manage-usage-limits-and-overages-in-chatgpt-enterprise-and-edu) and the [spend-controls walkthrough](https://vimeo.com/1207484127/0f2029dd01?share=copy&fl=sv&fe=ci). ## Incident and revocation controls ### How can admins stop access or activity? During user removal or incident review, admins might need to stop access, disable apps, revoke shared credentials, pause scheduled tasks, or revoke Codex credentials. Revocation paths include: * Remove a user’s workspace or group access. For SCIM-managed users, remove access at the identity provider; otherwise, a later synchronization can provision the user again. * Disable or restrict the relevant plugin or app. * Revoke a shared connection, bot, or service account through its owning surface. Workspace owners and admins can separately revoke Codex workspace access tokens. * Remove a Workspace Agent from publication or delete it through its agent owner or workspace administrator. * Disable the relevant scheduled task or, where available, Workspace Agent API trigger. * For Codex access, separately revoke the relevant access token, repository connection, and cloud-environment access. Managed configuration isn’t an access-revocation mechanism. ## Additional resources for your teams | Topic | Use this when explaining | Learn ChatGPT page | | --- | --- | --- | | Work overview | How cloud execution, browser access, network policy, and data boundaries work | [ChatGPT Work Overview](https://developers.openai.com/codex/enterprise/chatgpt-work-overview) | | Workspace setup and RBAC | Who can use and administer Codex | [Admin rollout guide](https://developers.openai.com/codex/enterprise/admin-setup) | | Authentication | How ChatGPT sign-in, API key sign-in, and workspace policy differ | [Authentication](https://developers.openai.com/codex/auth) | | Approvals and sandboxing | How Codex controls file, command, network, and side-effecting tool actions | [Agent approvals and security](https://developers.openai.com/codex/agent-approvals-security) | | Managed policy | How admins enforce Codex settings users can’t override | [Managed configuration](https://developers.openai.com/codex/enterprise/managed-configuration) | | Runtime environments | How Codex cloud setup, secrets, caches, and task phases work | [Cloud environments](https://developers.openai.com/codex/environments/cloud-environment) | | Internet access | How Codex cloud domain allowlists and HTTP methods work | [Agent internet access](https://developers.openai.com/codex/cloud/internet-access) | | Permissions | How filesystem, network, and deny-read controls work | [Permissions](https://developers.openai.com/codex/permissions) | | Observability | How analytics, reporting, and compliance exports work | [Governance](https://developers.openai.com/codex/enterprise/governance) | | Automation credentials | How access tokens are created, limited, revoked, and audited | [Access tokens](https://developers.openai.com/codex/enterprise/access-tokens) | ## Recommended admin actions * **Confirm who should have access first.** Decide whether to restrict access to ChatGPT Work, run a pilot, or roll it out broadly. Many organizations start with power users, champions, or teams with clear use cases. * **Review roles and permissions.** In **Permissions & roles**, confirm which users or groups can access ChatGPT Work. Match access to business need, readiness, and governance expectations. * **Review plugins and data sources.** ChatGPT Work is most useful with approved business context such as files, email, calendars, Slack, or CRM. Review enabled plugins, their audiences, and whether app policies still match how users should delegate work. * **Set expectations for appropriate use cases.** Position ChatGPT Work for multi-step, higher-value tasks such as research, synthesis, analysis, file creation, workflow updates, and reusable outputs. Use Chat for quick questions, light rewrites, or brainstorming. * **Review credit and usage controls.** Because ChatGPT Work can perform longer-running tasks, it can use more credits than a standard Chat conversation. Review defaults, group defaults, user overrides, and internal guidance about matching effort to business value. * **Identify your first high-value workflows.** Start with clear, reviewable outcomes such as customer briefings, recurring reports, research synthesis, tracker updates, or polished documents and slides. * **Prepare champions and support teams.** Give champions, training leads, and support teams rollout resources first so they can answer questions, collect feedback, and model effective delegation. * **Communicate review and approval expectations.** Remind users that people remain responsible for reviewing outputs, validating important claims, and approving consequential actions before they are shared or used. * **Monitor adoption and adjust.** Review usage, feedback, credit consumption, and delegated work after rollout. Use the findings to adjust access, guidance, training, and expansion. Ask AI ## Docs agent Loading docs agent...