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If ChatGPT or Claude is blocked on your work network, do not switch to a personal account or another public chatbot on your own. The reliable route is to ask your IT help desk, security team, or intranet service catalog which AI tools are approved for your department, account, device, and data classification. Use the organization’s work tenant and follow its retention, logging, human-review, and disclosure rules. Common approved options include Microsoft Copilot in Microsoft 365, Gemini where Google Workspace is enabled, an internally hosted assistant, or a governed coding assistant. Approval is specific to the employer and use case, so a tool that works for one department may be prohibited for another.
What should I do first when ChatGPT or Claude is blocked at work?
Start with your employer’s policy and approved-service list, not with a search for a substitute website. A blocked page usually signals an authorization or data-governance decision; it does not mean that any unblocked AI service is safe to use.
- Open the right source of truth. Search the intranet for “generative AI,” “AI tools,” “acceptable use,” “approved software,” or “service catalog.” If those pages are unclear, open an IT or security help-desk ticket.
- Describe the actual need. State whether you need document drafting, summarization, coding, analysis, translation, or a custom agent. Approval can differ by task even when the product name is the same.
- Identify your scope. Include your department, country or region, device type, employment status, and whether you need a browser service, desktop application, extension, API, or integrated workplace feature.
- Confirm the exact account. Ask for the product name, edition, license, sign-in method, and tenant. A work-enabled tenant may have controls and contractual terms that a consumer account does not.
- Ask what information is allowed. Obtain the permitted data classification before uploading files or pasting text.
Microsoft workplace guidance gives the plain-language rule: “Use only company-authorized AI services.” It also advises avoiding confidential company details and checking AI-generated results before relying on them. Treat those as baseline controls even when your employer’s policy is more detailed.
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Why can one department use an AI tool while another cannot?
AI approval is organization-specific. Departments may use different tenants, contracts, data classifications, risk tolerances, or regulatory controls, so “approved” is never a universal label.
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UK government examples illustrate the variation. The Department for Education encourages Microsoft Copilot Chat and sanctions Claude only for limited technical staff. The Cabinet Office approved Gemini through its Google Workspace. The Department for Energy Security and Net Zero provides Microsoft 365 Copilot. HM Treasury uses an internal HMT-GPT built on Claude and ChatGPT alongside Copilot. Defra permits Microsoft Copilot while allowing Gemini, Claude, and Grok only for controlled exploration. Consumer editions are not permitted for official business unless they have been specifically assured and approved.
Use these examples as a warning against copying another team’s setup. Ask your own AI owner which product, tenant, feature set, and data types are authorized for your role.
How do I verify that an AI tool is actually approved?
Approval should be verifiable through a named owner, an official catalog entry, or a written response from IT, security, privacy, or legal. A colleague’s experience, a browser login that happens to work, or an app-store listing is not proof of authorization.
Check the product and tenant
- Record the exact product and edition, such as a workplace or enterprise version rather than a consumer service.
- Confirm that your organization owns or administers the tenant.
- Use the prescribed single sign-on or work account. Do not create a personal account to bypass a sign-in restriction.
- Ask whether browser access, mobile access, desktop applications, plug-ins, APIs, agents, and file uploads are separately enabled.
Check the policy record
- Find the policy version, effective date, and approving function.
- Look for a named service owner or support queue.
- Confirm whether approval covers your department, geography, employment type, and device.
- Save the written answer or catalog reference for your project records.
Check the allowed use case
An approved service may still forbid automated decisions, customer-facing text without review, regulated records, source-code uploads, or use outside a controlled pilot. Ask whether your proposed workflow is allowed, not merely whether the product appears on a list.
What data can I enter into an approved AI service?
Use the lowest-risk data that still lets you complete the task. Oregon’s published FAQ permits only Level 1 (“Published”) and Level 2 (“Limited”) data in approved generative-AI tools. Level 3 (“Restricted”), Level 4 (“Critical”), and regulated data must not be entered. Your employer may use different labels, so map its classifications before using an AI feature.
Build a data decision before you prompt
- Classify the input. Determine whether it is public, internal, confidential, personal, regulated, security-sensitive, or mission-critical.
- Remove unnecessary detail. Redact names, account numbers, credentials, customer identifiers, unpublished financial figures, and proprietary code when they are not essential.
- Check the feature boundary. File upload, connectors, browsing, memory, plug-ins, and agent actions may have different rules from plain text chat.
- Confirm retention and training terms. Ask how prompts, files, outputs, and telemetry are retained, who can access them, and whether they are used to train a model.
- Escalate uncertainty. Stop and ask security, privacy, legal, or the designated AI owner when classification is unclear.
Do not assume that an enterprise label automatically makes every input acceptable. A work tenant can preserve identity and permissions while still enforcing restrictions on confidential or regulated information.
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Which governance controls should I ask about?
Before relying on an approved service, establish how the organization controls access, records activity, and responds to errors or incidents. Australian Government Digital Transformation Agency guidance recommends a risk-based approach to public generative-AI access, including technical controls, training, monitoring, and human validation.
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Identity and access
- Is single sign-on required, and can administrators disable personal accounts?
- Are access rights limited by department, role, geography, or device posture?
- Can administrators revoke access when someone changes role or leaves?
Data protection
- What retention period applies to prompts, uploads, outputs, and logs?
- Are prompts excluded from model training by contract and configuration?
- Are encryption, regional processing, deletion, and subprocessor requirements documented?
- Do upload blockers or data-loss-prevention rules prevent prohibited content?
Oversight and accountability
- Are prompts and actions logged for audit, and who can review them?
- When is human approval mandatory before publication, payment, access changes, or other consequential action?
- How must users disclose AI assistance to customers, colleagues, regulators, or records managers?
- Where do you report a data leak, unsafe output, biased result, or service failure?
Keep a short record of the answers for each workflow. Controls can change when a license, model, connector, or regional setting changes.
Can I use Microsoft Copilot at work?
Microsoft Copilot and Microsoft 365 Copilot are often practical alternatives in organizations that already run Microsoft 365, but access is approved only when your employer has enabled the relevant product and tenant. Work-account access can preserve existing file and permission controls; it does not grant permission to use every connected document or feature.
Verify before using it
- Confirm whether your organization provides Copilot Chat, Microsoft 365 Copilot, or another edition.
- Check whether your license includes the applications, connectors, agents, and file-grounding features you need.
- Ask whether prompts and generated content are logged and how existing SharePoint, OneDrive, Teams, or mailbox permissions are enforced.
- Use only documents you are already authorized to access, and review sharing settings before distributing an output.
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Start with low-risk drafting, meeting-note cleanup, or a summary of documents you are allowed to read. Verify names, dates, calculations, quotations, citations, and action owners before sending the result.
Can I use Gemini for Google Workspace instead?
Gemini can be an approved choice where the organization runs Google Workspace and has enabled Gemini under its administrative controls. The Cabinet Office example shows that a department may select this route instead of Microsoft’s tools.
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What if my employer provides an internal AI assistant?
An internal or assured enterprise chatbot may be the safest option when it is operated by your organization and configured for its data rules. HM Treasury’s HMT-GPT is an example of an internal assistant built on approved models, including Claude and ChatGPT, alongside Copilot.
Internal deployment does not remove the need for review. Confirm the assistant’s approved data classes, retention schedule, access groups, model or connector boundaries, output-review rules, and incident channel. Use the internal service for the tasks it was designed to support rather than assuming it is a general-purpose replacement for every public chatbot.
What is the approved option for software developers?
Developers should ask for a governed coding-assistant setup rather than installing an extension independently. GitHub Copilot with enterprise controls can let administrators restrict approved GitHub organizations, disable agents or extensions, choose a default model, and control Claude integrations.
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- Are repositories, tickets, secrets, and production logs excluded from prompts and indexing?
- Which organizations, repositories, branches, models, agents, and extensions are allowed?
- Can administrators audit suggestions, chats, tool calls, and generated pull requests?
- What review is required for licensing, security, vulnerability, and test coverage issues?
- Are developers allowed to use local models or command-line tools, and under what data restrictions?
Review generated code like code from an unfamiliar contributor: run tests, inspect dependencies and licenses, check for insecure patterns, and require normal peer review before merge.
When does Copilot Studio make sense?
Copilot Studio can support governed internal agents for larger organizations, but it is an implementation project rather than a quick workaround for a blocked website. Licensing, funding, identity integration, security controls, data connectors, testing, monitoring, and ongoing ownership are required.
Submit a business case when the workflow needs repeatable actions, approved enterprise data, role-based access, or auditability that a chat window cannot provide. Define the agent’s purpose, permitted sources, prohibited actions, escalation path, human approvals, success measures, and retirement plan before requesting build resources.
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How should I compare approved AI tools?
Compare services against the workflow and the organization’s controls, not against headline model capability alone. Use the same questions for every candidate so that a familiar brand does not hide a governance gap.
| Decision area | What to verify | Why it matters |
|---|---|---|
| Identity and tenant | Work sign-in, tenant ownership, role-based access, account lifecycle | Prevents personal use and limits who can reach data and features |
| Retention and training | Prompt, file, output, and telemetry retention; model-training terms | Determines whether sensitive material persists or is reused |
| Workplace integration | Microsoft 365 or Google Workspace connections, permissions, connectors | Controls what the assistant can retrieve and where it can write |
| Administrator controls | Feature switches, model selection, agent and extension restrictions | Lets the organization enforce a consistent configuration |
| Audit and logging | Access logs, prompt or action records, export and review capability | Supports investigations, compliance, and accountability |
| Data classification | Explicitly permitted and prohibited levels, regions, and regulated data | Stops users from guessing whether an input is safe |
| Human review | Required checks, disclosure language, approval gates | Reduces harm from inaccurate, biased, or incomplete output |
| Accessibility and region | Language, assistive-technology support, service availability, processing region | Ensures the tool works for the people and locations covered |
| Licensing and support | Named owner, cost center, service levels, training, incident route | Prevents an unsupported pilot from becoming an unmanaged dependency |
| Task fit | General chat, document work, coding, analysis, or custom agents | Matches capability and risk controls to the actual job |
What should I do if the approved catalog has no suitable tool?
Do not work around the block. Submit a business case or exception request through IT, security, privacy, legal, procurement, or the designated AI governance team.
Include these details
- The business problem, users, department, and expected frequency.
- The smallest data set and lowest-risk prototype that could demonstrate value.
- Required integrations, regions, accessibility needs, retention period, and support model.
- How outputs will be reviewed, disclosed, corrected, and removed.
- Security risks, failure consequences, human fallback, and a proposed end date for the pilot.
Ask whether an existing approved service can meet the need with a different configuration. A controlled pilot may be approved even when open-ended public use is not.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What practices are prohibited even when another service is reachable?
Network availability is not authorization. Avoid these common failures:
- Signing into a personal account to avoid a work restriction.
- Pasting confidential, personal, regulated, restricted, or critical information into a public chatbot.
- Installing an unapproved browser extension, desktop client, plug-in, model, or agent.
- Uploading a whole repository, mailbox, customer export, or shared drive when a redacted excerpt would suffice.
- Trying to defeat network controls, DNS blocks, endpoint policies, or monitoring.
- Publishing AI-generated text, code, analysis, or decisions without the review required by policy.
If you already entered sensitive information, stop using the service, preserve the relevant details, and report the incident through your organization’s security or privacy channel. Do not delete evidence or attempt a private fix that could delay response.
How can I start safely while waiting for approval?
Use non-sensitive practice material and an approved productivity feature, if one exists, while your request is evaluated. A useful pilot can be built from public documents, synthetic records, or manually redacted examples.
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- Write a one-page use-case description with the task, inputs, outputs, users, and human reviewer.
- Classify every input and remove fields that are not needed.
- Test for factual errors, invented citations, missing context, biased wording, and unsafe recommendations.
- Measure time saved and correction effort rather than treating fluent text as proof of quality.
- Document the prompt pattern, version or feature used, reviewer sign-off, and known failure cases.
- Stop the pilot if the service changes terms, loses required controls, or produces an unacceptable risk.
How do I validate an AI answer before using it?
Validation is part of the workflow, not an optional final glance. Microsoft guidance explicitly warns that AI can make mistakes.
- Check factual claims against the authoritative document, system, or subject-matter expert.
- Recalculate numbers and inspect units, dates, assumptions, and missing rows.
- Open every cited source and confirm that it actually supports the statement.
- Review code in a test environment for security, licensing, performance, and maintainability.
- Look for personal data, confidential details, discriminatory language, and unsupported certainty.
- Record who reviewed the output and what was changed when the workflow is consequential.
For decisions affecting employment, finance, health, safety, access, or legal rights, follow the stricter human-review and documentation rules that apply to that domain.
How do I explain the request to IT or security?
A precise request gets a faster and safer answer than “Can I use an AI tool?” Include the following in a ticket:
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Account and device: [work tenant, browser, desktop, mobile, API]
Data classes: [what enters the tool, with redaction plan]
Integrations: [mail, files, repositories, tickets, or none]
Output and reviewer: [where the result goes and who checks it]
Retention, region, and disclosure needs: [known requirements]
Fallback: [manual process if the service is unavailable]Ask for a written yes, no, or conditional approval and the conditions that make it valid. This creates an auditable decision instead of relying on informal advice.
Frequently Asked Questions
Can I use an AI tool on my phone if the desktop site is blocked?
Only if your employer has approved the mobile app, account, device posture, and network path. Mobile access can bypass desktop controls and may store cached prompts or files, so ask IT before installing or signing in.
Does an incognito window make an unapproved chatbot acceptable?
No. Private browsing changes local history, not authorization, retention, or the service’s handling of your data. Your employer’s policy still applies, and network or security logs may still record the connection.
Who owns an AI-generated document created in an approved workplace tool?
Ownership, records retention, and intellectual-property treatment depend on your employer’s policy, contracts, and local law. Save the approved source materials, reviewer changes, and final version according to your normal records process rather than treating the chat transcript as the only record.
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Can I ask an approved tool to connect to a third-party app?
Only when that connector, app, and data flow are explicitly enabled by administrators. A connector can export information to another service or grant write access, so approval for the core chatbot does not automatically cover every integration.
What should I do when an AI answer conflicts with an official source?
Treat the official source as authoritative, do not publish the disputed answer, and record the discrepancy if the workflow is monitored. Report repeated or high-impact errors to the service owner so prompts, retrieval sources, or controls can be corrected.
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