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Secure an AI tool before you enter work information, not after. First confirm that the exact service, account type, and intended use are approved by your employer. Then verify how that service handles prompts and files, sign in through the organization’s managed identity system, use a compliant device and phishing-resistant multifactor authentication (MFA) where required, limit connected permissions, and keep a person responsible for checking consequential output.
There is no universal “safe AI” setting. Retention, provider access, administrator visibility, logging, integrations, and regulatory controls vary by product, plan, region, and employer configuration. The checklist below gives you a practical way to make the decision without assuming that a consumer account and a managed workplace deployment behave the same way.
1. Get approval for the exact tool, account and task
Approval is the first control. Ask your manager, security team or data owner whether the specific AI service and account are approved for the work you want to perform. An employer-managed deployment may be governed by different contracts, retention settings and administrative controls than a personal account for the same service.
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- Is this exact product and edition approved for business use?
- Must I use an organization-managed account, single sign-on (SSO) or a particular sign-in URL?
- Is my intended task allowed for the data classification involved?
- Are there device, network, location or browser requirements?
- What activity is logged, who can review it, and how long are logs retained?
- Which actions require human approval before anything is sent, changed or published?
If nobody can answer, pause. Do not treat popularity or a free trial as evidence of approval. Microsoft’s guidance on securing generative-AI applications emphasizes organization-level governance, controlled access and lifecycle management rather than a universal approved-tool list.
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2. Check how the service handles your data
Data handling is tool-specific. Read the current terms and your employer’s configuration for the exact plan you will use. Look for four separate issues: retention of prompts and uploaded files, provider or subcontractor access, whether submissions can be used to improve a service, and the administrator controls available to your employer.
Use the right account
Do not assume that turning off a setting in a personal account changes the policy for an employer-managed tenant, or vice versa. Capture the plan name and configuration your organization approved, and ask IT which settings are enforced centrally. If terms are unclear, submit only information that is already public or non-sensitive until the data owner gives written permission.
Apply your workplace classification rules
Before copying text, classify it under your employer’s policy. Secrets, passwords, private keys, authentication codes, personal information, customer records, unreleased financial results, regulated data and confidential contracts should be treated as prohibited unless the organization explicitly permits that category in the approved service. When a classification or permission is uncertain, ask the data owner or security team rather than guessing.
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Removing a conversation from your interface may not remove security logs, backups, administrator records or copies created by an integration. Ask what deletion means for prompts, files, exports and audit trails, and whether legal-retention requirements override ordinary deletion.
3. Use a pre-submission checklist
Run this check every time the information is not clearly public. It is short enough for routine use and conservative enough for unfamiliar tools.
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- Identify the destination. Confirm the product, workspace, account and browser extension receiving the information.
- Classify the content. Remove secrets and unnecessary personal, customer or regulated details. Replace real identifiers with synthetic examples where possible.
- Confirm permission. Check that the approved service accepts this classification and that your role allows you to disclose the material.
- Minimize the input. Send only the passages and fields needed for the task, not an entire repository or mailbox.
- Inspect the response. Treat generated text, citations, code and extracted facts as untrusted until checked against authoritative sources.
- Record the decision when required. For regulated or high-impact work, keep the human review and approval evidence required by your organization.
4. Secure files, connectors and AI actions
An assistant can often retrieve information that the signed-in user is already allowed to access. If shared folders, sites or repositories are overshared, connecting an AI tool can make that exposure easier to discover. Microsoft’s Copilot deployment guidance therefore puts oversharing remediation, guardrails and regulatory protections ahead of broad rollout. Those controls are product-specific examples, not a promise that another service has the same features.
Review what the AI can reach
- List every file store, application, mailbox, database and website connected to the tool.
- Remove stale group membership and broad shared links before enabling retrieval.
- Use a dedicated connection or service identity with only the permissions required for the task.
- Set an expiration date or review date for temporary access.
- Revoke unused connectors when the project ends or a person changes role.
Treat retrieved instructions as untrusted
Text in a document, web page or ticket can contain instructions aimed at manipulating the model. It does not override workplace policy. Verify unexpected requests for secrets, external uploads, payment changes, privilege escalation or mass deletion through a separate trusted channel.
Put people in front of consequential actions
For agents that can send messages, edit records, approve transactions, deploy code or trigger workflows, define which actions require human confirmation. Ask what event data is logged, whether a dry-run mode exists, how failed actions are rolled back and who receives alerts. Microsoft’s AI defense catalog groups the relevant principles under least privilege, input and retrieval hygiene, runtime containment and monitoring; exact controls depend on the service.
5. Protect the account and device
Use managed identity and a compliant device
Sign in through the employer’s SSO or identity portal when required. A managed device can enforce encryption, screen-lock, patching, endpoint protection and data-loss-prevention rules that a personal computer cannot. Do not bypass a compliance check by creating a personal account.
Enable strong MFA
Use the strongest method supported by your organization. Microsoft Learn’s “Secure Generative AI with Microsoft Entra” guidance, last updated June 20, 2025, says: “Require users to complete phishing-resistant multifactor authentication (MFA) to access Gen AI apps.” CISA’s business guidance identifies a physical security key as one possible phishing-resistant method: “Security key: Use a physical security key (like a YubiKey) to log in.” Compatibility depends on your identity provider, account type, device and employer policy, so confirm support before purchasing or enrolling hardware.
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Keep authentication private
- Never share an account, password, recovery code or MFA approval.
- Reject unexpected sign-in prompts and report them through the company’s security channel.
- Install updates for the operating system, browser and approved AI client.
- Check browser extensions and remove unapproved extensions that can read page content.
- Lock the screen when leaving a device with an AI session open.
Review access over the employee lifecycle
Ask whether the organization performs periodic access reviews and removes permissions when a role changes or employment ends. Microsoft’s identity guidance specifically addresses lifecycle management, access reviews and reducing standing privilege.
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6. Understand employer visibility
Whether an employer can see prompts, files or outputs depends on the account, contract, administrator settings, identity provider, network controls and logging implemented for that service. Some workplaces may record sign-ins, uploads, connector activity, moderation events or workflow actions; others may have less visibility. Do not assume that a personal account is private on a managed device or network, and do not assume that an enterprise account exposes every prompt to an administrator.
Ask for the written monitoring and privacy notice that applies to your deployment. It should explain what is collected, the purpose, retention period, access roles and escalation process. Use the approved account for work and keep personal experimentation separate.
7. Verify every consequential answer
Security is not only about preventing data leakage. AI output can be wrong, outdated, biased or based on malicious retrieved content. For legal, medical, financial, employment, safety, customer-impacting or production decisions:
- Check claims against the authoritative policy, record or primary source.
- Run code through the organization’s review, testing and dependency checks.
- Confirm calculations independently, especially when units, currencies or dates matter.
- Have a qualified person approve the final communication or action.
- Preserve the required human-review record instead of presenting generated text as evidence.
8. A rollout checklist for managers and administrators
Before enabling an AI service for a team, establish controls at the organization level rather than relying on individual caution.
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- Inventory. Identify sanctioned services, shadow deployments, accounts, connectors, agents and data stores.
- Define use cases. Map each use case to data classifications, prohibited actions, required reviewers and retention obligations.
- Control identity. Require managed accounts, least privilege, Conditional Access, compliant-device checks and phishing-resistant MFA where supported.
- Remediate oversharing. Review shared files, sites and groups before an assistant can retrieve them.
- Set guardrails. Restrict high-risk connectors, external sharing, autonomous actions and unapproved browser extensions.
- Monitor. Collect enough audit data to investigate misuse without retaining more sensitive content than necessary.
- Prepare response. Define how to revoke tokens, disconnect an integration, preserve evidence, notify affected parties and restore changed records.
- Review continuously. Reassess permissions, terms, models, connectors and regulatory requirements when the service or workforce changes.
Microsoft’s Copilot guidance describes a secure data foundation that includes oversharing remediation and Purview protections, plus a broader defense-in-depth approach. These are examples for that product family, not evidence that every AI service offers equivalent controls.
9. Which security frameworks apply?
NIST SP 1800-35
NIST SP 1800-35, dated June 2025, is a Zero Trust implementation practice guide for enterprise resources across on-premises and cloud environments, hybrid workers and partners. It is useful for architecture and access planning, but it is not an employee checklist specific to AI chat tools.
NIST SP 800-218A
NIST SP 800-218A, dated July 2024, adds generative-AI practices to the Secure Software Development Framework for organizations producing or acquiring AI models and systems. It is most relevant when your organization builds or procures AI, rather than when an employee simply uses a managed chatbot.
Google Secure AI Framework
Google’s Secure AI Framework (SAIF) is a vendor framework for security and privacy in AI applications. It stresses that the business problem and the data needed should determine the controls. Use it as an additional perspective, not as a neutral certification of a particular workplace product.
10. Compare candidate tools on controls, not slogans
If your organization is choosing between services, require written answers for the same questions. Product-specific retention, training-use and feature claims cannot be inferred for unnamed tools.
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- POWERFUL SECURITY KEY: The Security Key C NFC is the essential physical passkey for protecting your digital life from phishing attacks. It ensures only you can access your accounts.
- WORKS WITH 1000+ ACCOUNTS: Compatible with Google, Microsoft, and Apple. A single Security Key C NFC secures 100 of your favorite accounts, including email, password managers, and more.
- FAST & CONVENIENT LOGIN: Plug in your Security Key C NFC via USB-C and tap it, or tap it against your phone (NFC) to authenticate. No batteries, no internet connection, and no extra fees required.
- TRUSTED PASSKEY TECHNOLOGY: Uses the latest passkey standards (FIDO2/WebAuthn & FIDO U2F) but does not support One-Time Passwords. For complex needs, check out the YubiKey 5 Series.
| Criterion | What to verify | Why it matters |
|---|---|---|
| Employer approval and account control | Can IT provision, suspend and audit users centrally? | Separates governed deployments from unmanaged personal accounts. |
| Data handling | Current retention, provider access and submission-use terms for the exact plan and configuration | Determines where prompts and files may persist or be viewed. |
| Data boundaries | Can shared files and sites be reviewed, narrowed and monitored? | Reduces exposure caused by overshared underlying data. |
| Identity and device controls | Support for SSO, Conditional Access, compliant-device checks, lifecycle reviews and strong MFA | Limits account takeover and standing access. |
| Connected tools and actions | Permission scoping, runtime containment, approval gates and activity logs | Constrains what an agent can do if an input or model is manipulated. |
| Governance | Ability to meet regulatory, audit, records and data-loss-prevention requirements | Makes the deployment defensible for high-impact work. |
11. What to do when something goes wrong
You pasted sensitive information
Stop using the session, note exactly what was submitted and when, and contact the security or privacy team immediately. Do not attempt to conceal the incident by deleting local evidence. Follow the organization’s breach-reporting process; the team may need to revoke tokens, request provider deletion, preserve logs or notify affected parties.
The AI requests a secret or an unexpected action
Refuse the request, stop the workflow and verify it with the document owner or administrator. Treat the content as a possible prompt-injection attempt, especially when it asks you to ignore policy, reveal hidden instructions or contact an unknown destination.
A connector exposes too much data
Disable or disconnect it if your policy permits, preserve the configuration and notify the administrator. Ask for a permissions review covering the source repository, groups, shared links, service identity and cached results.
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Deny it, change the password through the approved identity portal if instructed, and report the event. Do not approve a prompt merely to make an AI tool work.
12. A simple go/no-go decision
- Approved? If the service, account or use case is not explicitly approved, stop.
- Permitted data? If classification, retention or provider access is unknown, use sanitized public material or ask the data owner.
- Controlled access? If managed identity, MFA, device and connector permissions cannot be enforced, do not connect sensitive systems.
- Human oversight? If the tool can make a consequential decision or action without an appropriate reviewer, redesign the workflow.
- Auditable? If nobody can determine what was accessed, changed or sent, limit the use to low-risk experimentation until logging and response procedures exist.
This approach aligns with the control areas emphasized by Microsoft, NIST, Google and CISA while leaving product-specific settings to the employer and service administrator.
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