Artificial intelligence tools are now part of daily life—from chatbots and virtual assistants to recommendation engines and productivity apps. While these systems can boost efficiency, they also introduce risks to your personal and business data if misused. Understanding what not to share with AI is essential, especially if you operate a U.S.-based website or business subject to regulations like HIPAA, GLBA, COPPA, and state privacy laws such as the California Consumer Privacy Act (CCPA/CPRA). This guide explains the categories of data you should never provide to AI tools, why those risks matter, and practical steps to stay compliant and secure.
Why AI Privacy Risks Are Unique
Many AI services process data in the cloud, store logs for model improvement, and sometimes involve third-party vendors. Even when a provider claims to protect your information, misconfiguration, supply chain risk, or accidental prompts can expose sensitive details. In addition, AI models can memorize rare inputs and regurgitate them unexpectedly, a phenomenon known as “training data leakage.” The safest posture is data minimization: only share what is strictly necessary and never share regulated or high-risk data.
1) Personally Identifiable Information (PII)
Do not share:
- Full names combined with other identifiers
- Home address, email, phone numbers
- Driver’s license numbers, passport numbers, Social Security numbers (SSN)
- Date of birth, place of birth, mother’s maiden name
Why it matters: PII enables identity theft, account takeover, and targeted scams. Under U.S. state privacy laws (e.g., CCPA/CPRA, Virginia CDPA, Colorado CPA), PII is protected, and breaches can trigger disclosure obligations and penalties.
Safer alternative: De-identify the data. Replace names with roles (e.g., “Customer A”), mask dates (YYYY only), and remove direct identifiers before using AI tools.
2) Financial and Payment Data
Do not share:
- Credit/debit card numbers, CVV codes, bank account and routing numbers
- Investment account numbers, crypto private keys, tax returns
- Detailed transaction histories tied to individuals
Why it matters: Payment data is governed by PCI DSS and state data breach laws. Exposure can lead to fraud and legal liability. Tax documents often include SSNs and employer information—high-risk targets for attackers.
Safer alternative: Summarize financial patterns without raw account numbers or transaction-level details. Use ranges (“$10–15M revenue”) instead of precise figures tied to a client.
3) Health Information (PHI)
Do not share:
- Medical histories, lab results, prescriptions linked to a person
- Insurance member IDs, appointment details with names
- Any data that could identify a patient combined with health information
Why it matters: HIPAA covers protected health information. Sharing PHI with non-HIPAA compliant AI tools can constitute a breach. Even “innocent” symptom narratives can become PHI when linked to identifiable data.
Safer alternative: Use synthetic or anonymized cases. Strip all identifiers and ensure the data cannot be re-linked to a person.
4) Authentication Secrets and Security Details
Do not share:
- Passwords, API keys, OAuth tokens, private SSH keys
- One-time passcodes, recovery phrases, secret questions/answers
- Internal security architecture diagrams, unpatched vulnerability details
Why it matters: These secrets grant direct access to systems and data. Even momentary exposure in a prompt can be logged. If a key is ever pasted into an AI tool, immediately revoke and rotate it.
Safer alternative: Discuss patterns, not secrets. If you need code help, replace keys with placeholders like “API_KEY_HERE.”
5) Confidential Business Information
Do not share:
- Unreleased product roadmaps, pricing strategies, contracts under NDA
- M&A plans, investor decks, board communications
- Source code, proprietary algorithms, model weights
- Customer lists and CRM exports
Why it matters: Trade secrets lose protection when disclosed publicly or to third parties without proper safeguards. Some AI vendors retain prompts for quality improvement, which can increase exposure risk.
Safer alternative: Abstract your question. Provide minimal, non-identifying snippets. Use on-prem or enterprise AI with strict data retention controls and a Business Associate Agreement (BAA) or Data Processing Addendum (DPA) where applicable.
6) Data About Children
Do not share:
- Names, school information, photos, voice samples, or location data of minors
- Behavioral or educational records
Why it matters: COPPA regulates data about children under 13 in the U.S. Collecting or processing such data without verifiable parental consent can lead to significant penalties.
Safer alternative: Aggregate and anonymize. Avoid uploading any child-specific content unless your AI tooling is explicitly COPPA-compliant.
7) Location and Biometric Data
Do not share:
- Precise GPS coordinates, geofenced home/work patterns
- Face photos tied to identity, voiceprints, fingerprints, iris scans
Why it matters: Location data can reveal home addresses, routines, and sensitive visits (clinics, places of worship). Biometric data is highly sensitive and protected in several states (e.g., Illinois BIPA, Texas, Washington).
Safer alternative: Use coarse locations (city/state) and remove timestamps. Avoid biometric uploads unless you have explicit consent and compliant tooling.
8) Government-Issued and Sensitive Legal Information
Do not share:
- Social Security cards, green cards, immigration case numbers
- Subpoenas, sealed records, attorney–client privileged communications
Why it matters: Legal privilege can be waived by disclosure to third parties. Government IDs are prized by fraudsters and can enable synthetic identity schemes.
Safer alternative: Consult counsel before using AI with privileged documents. If you must summarize, extract non-sensitive, high-level points offline first.
9) Education and Employment Records
Do not share:
- Transcripts, student IDs, HR files, performance reviews
- Salary histories tied to individuals, background checks
Why it matters: FERPA protects education records; employment data is sensitive and often subject to state privacy requirements and company policies.
Safer alternative: Provide role-based, anonymized summaries (e.g., “three mid-level engineers” instead of names with reviews).
10) High-Risk Media and Metadata
Do not share:
- Photos of your workspace with whiteboards or visible monitors
- Screenshots containing tabs, filenames, meeting links, or calendar invites
- Document EXIF metadata revealing device IDs or GPS
Why it matters: Images and PDFs often contain hidden metadata. Screens can leak meeting IDs, client names, or internal systems.
Safer alternative: Redact before upload. Strip metadata, blur sensitive areas, and verify screenshots carefully.
Practical Safeguards for U.S.-Based Sites and Teams
- Classify data: Label assets as Public, Internal, Confidential, Restricted. Prohibit Restricted data in general-purpose AI.
- Use enterprise controls: Prefer vendors offering data retention opt-out, SOC 2/ISO 27001, SSO, audit logs, and region pinning.
- Minimize prompts: Share the smallest possible dataset. Summarize and tokenize identifiers.
- Anonymize and synthesize: Use synthetic datasets for modeling or testing when real data isn’t necessary.
- Contract for privacy: Execute DPAs/BAAs where applicable. Ensure subprocessors and cross-border transfers are disclosed and compliant.
- Rotate secrets: If any secret touches an AI prompt, revoke and rotate immediately.
- Implement DLP: Use data loss prevention at the browser and network layers to block uploads of sensitive patterns (e.g., SSNs).
- Train teams: Provide prompt hygiene training and clear “do not share” examples.
- Log and review: Maintain records of what is sent to AI tools, by whom, and for what purpose.
- Respect user rights: If you process consumer data, support deletion, correction, and access requests per CCPA/CPRA and other state laws.
Red Flags That Mean “Stop”
- The AI tool cannot clearly state how it stores, encrypts, or deletes your inputs.
- The provider reuses prompts for training without an enterprise opt-out.
- You cannot sign a DPA/BAA where legally necessary.
- The model or plugin requests broad access to your drive, email, or calendar.
A Simple Mental Checklist Before You Paste
- Could this data identify a person?
- Could this create financial, legal, or reputational risk if leaked?
- Is there a way to summarize or anonymize it first?
- Do I have explicit consent and a compliant vendor?
By consistently applying these principles, you’ll reduce the risk of data leakage, align with U.S. privacy expectations, and build trust with your users and customers.
