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Do not enter patient information into an AI tool until your organization has approved the specific workflow and verified what happens to the data. The answer depends on the organization using the tool, the tool’s role, the information submitted, the vendor and its subprocessors, the contract and configuration, and the applicable law. A product’s privacy notice or a claim that it is “HIPAA compliant” is not, by itself, permission to disclose protected health information (PHI).
For U.S. clinicians, the practical sequence is to classify the use, identify every data element and recipient, establish the HIPAA and organizational basis, review the vendor’s actual terms and technical controls, minimize the information shared, and require human oversight. Privacy officers and counsel should make the final determination, especially where state law, institutional policy, employment rules, or a particular contract adds requirements.
Why privacy decisions matter as clinical AI use grows
AI is already part of routine professional work for many physicians. The American Medical Association’s July 2026 overview reports that more than 80% of physicians use AI professionally, more than three-quarters say it improves their ability to care for patients, and about 40% feel both excited and concerned about AI’s role in health care. The figures come from the AMA’s stated survey context; they should not be treated as a universal measure for every specialty, organization, or country.
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Classify the exact AI use before discussing compliance
“AI medical tool” describes very different products. Start with the intended use and the workflow, not the marketing label.
| Use category | Examples of information involved | Questions to resolve |
|---|---|---|
| Administrative drafting or summarization | Messages, referral details, scheduling notes, or other text supplied by staff | Is the tool approved for the organization’s data, and does the vendor retain or reuse the text? |
| General-purpose chatbot | Prompts, pasted chart excerpts, uploaded files, and account or device metadata | Is the service offered on behalf of a regulated entity, or is it a consumer service outside the organization’s HIPAA controls? |
| Ambient documentation | Exam-room audio, transcripts, speaker identity, generated notes, and timestamps | Where are recordings and transcripts stored, who can access them, and when are they deleted? |
| EHR-integrated assistant | Patient context pulled from the record, user identity, audit events, and generated content | Which systems and subprocessors receive the data, and what controls apply to the integration? |
| Diagnostic or treatment-support product | Images, signals, measurements, history, and clinician-entered findings | What is the intended use, and does the product fall within the FDA’s medical-device framework? |
The AMA calls for policies that address both device and non-device AI uses. FDA status is a separate question from privacy status: a tool can be useful in a clinic without being a regulated device, and a regulated device still requires appropriate data governance.
Determine whether the information is PHI or identifying health information
List every input and output, including information that may be easy to overlook:
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- Names, dates of birth, addresses, medical-record numbers, and insurance details.
- Clinical narratives, diagnoses, medications, laboratory results, images, recordings, and transcripts.
- Free-text prompts that combine a condition with a rare date, location, occupation, or event.
- Account names, email addresses, IP addresses, device identifiers, cookies, and other metadata.
HHS explains that an IP address, email address, or device identifier can be part of individually identifiable health information when combined with health-related context. Deleting a patient’s name therefore does not automatically make a prompt anonymous. Ask whether the remaining combination could reasonably identify the person and whether the organization’s approved de-identification method has been met.
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Separate production use from testing. Use synthetic or properly de-identified material for demonstrations and configuration tests when that is appropriate. Do not paste identifiable records into a public service merely because the test seems small or temporary.
Understand what HIPAA does and does not cover
HIPAA follows regulated relationships and workflows
HIPAA applies to covered entities, business associates, PHI, and particular permitted uses and disclosures. It does not automatically protect health information everywhere it travels. HHS states that HIPAA generally does not protect information a person voluntarily enters into an app that was not developed or offered by or on behalf of a regulated entity, even when the information originally came from a medical record. Other federal or state laws may still apply.
That means a clinician’s access to a patient record does not, by itself, make every external AI service a HIPAA-covered destination. The organization must assess the relationship and the actual workflow before sending the information.
A business associate agreement is important but not a universal permission slip
If a vendor performs functions for a covered entity that involve PHI, the relationship may make the vendor a business associate. HHS says that status depends on the relationship, whether or not a required business associate agreement (BAA) has actually been signed. A BAA should address permitted uses and disclosures, safeguards, and incident reporting.
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A BAA does not authorize every possible disclosure. The covered entity must still have a Privacy Rule permission for the particular purpose or obtain an authorization when one is required. Have the organization’s privacy and security personnel determine both questions; do not infer permission from a sales representative’s description of the product.
Privacy notices and consent banners are not a substitute for a legal basis
HHS’s position is explicit: "The Privacy Rule does not permit disclosures of PHI to a tracking technology vendor based solely on a regulated entity informing individuals in its privacy policy, notice, or terms and conditions of use that it plans to make such disclosures." That statement concerns tracking-technology disclosures, but the underlying lesson is broader for implementation: posting a notice does not cure an otherwise impermissible disclosure.
The Federal Trade Commission separately requires companies to make clear, truthful statements about privacy practices. It advises: "Also, be upfront about your practices, tell consumers the whole truth, and don’t bury key facts in a privacy policy, a Terms of Use section, or other places where consumers aren’t likely to read and understand them." A banner that says data is protected does not answer what is stored, reused, reviewed, or shared.
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Request written answers that match the contract and the product configuration. The following is a practical diligence set synthesized from federal guidance and AMA policy, not a universal statutory checklist.
| Question | What a useful answer should identify |
|---|---|
| What exactly is collected? | Prompt text, audio, images, transcripts, generated outputs, account data, logs, and metadata, with optional fields distinguished from required ones. |
| Where does each item go? | The vendor’s systems, hosting regions where relevant, integrations, and every downstream processor that can receive the data. |
| How long is it retained? | Default retention, backup retention, deletion triggers, and whether the customer can set a shorter period. |
| May the vendor reuse the data? | Whether inputs or outputs are used for service improvement, analytics, advertising, or any purpose beyond the approved workflow. |
| Is model training allowed? | Whether customer data is used to train or fine-tune models, whether that setting is off by default, and whether it can be contractually prohibited. |
| Can people review submissions? | Which personnel or contractors can access content, for what reasons, and what approval, logging, and confidentiality controls apply. |
| How is access controlled? | Authentication, role-based permissions, customer separation, administrative access, and audit-log availability. |
| How is data protected? | Encryption in transit and at rest, key-management responsibilities, vulnerability handling, and relevant independent assurance information. |
| What happens after an incident? | Detection, investigation, customer notification, cooperation, evidence preservation, and the contractual reporting timeline. |
| Can the organization delete or retrieve data? | Self-service and contractual deletion, export formats, treatment of backups, and confirmation that downstream processors follow the request. |
Compare the answers with the exact edition, terms, settings, and integrations the organization will use. A product may offer a restricted enterprise configuration while its public version follows different rules.
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Use a repeatable approval workflow
- Describe the purpose. Write down whether the tool drafts an administrative message, summarizes a visit, records ambient audio, supports a clinical decision, or performs another task. Specify who operates it and whether the output enters the medical record or influences care.
- Map data and recipients. Inventory prompts, recordings, images, identifiers, generated content, logs, and metadata. Identify the vendor, hosting service, subprocessors, internal users, and any human reviewers.
- Ask privacy and security reviewers to establish the legal basis. Determine whether the organization is a covered entity, whether the vendor is acting as a business associate, whether a BAA is required, and which Privacy Rule permission or authorization supports the disclosure. Apply state law and organizational policy as well.
- Review contract and configuration. Match the vendor’s retention, deletion, reuse, training, access, encryption, audit, and incident terms to the proposed workflow. Turn off optional collection and model-improvement features when the approved use does not require them.
- Minimize the information. Use the minimum information necessary where that standard applies. Remove direct identifiers or use synthetic examples for testing when feasible. Never use an unapproved public tool for identifiable patient information.
- Train users and document approval. Give clinicians a clear policy for permitted tools, prohibited inputs, escalation, and reporting. Record the approved product version, account type, configuration, and responsible owner.
- Keep a clinician in control. Review generated notes, summaries, and recommendations for accuracy, omissions, unsupported statements, and inappropriate disclosure before they enter the record or affect care. AI output is not a substitute for professional judgment.
- Reassess after meaningful changes. Recheck data flows, terms, model features, integrations, permissions, and retention after a vendor update, new module, changed hosting arrangement, or expansion to a new clinical use.
Do not confuse privacy status with FDA device status
FDA states: "The FDA does not regulate AI as such; it regulates medical devices, including AI-enabled medical devices." Whether a product is a device depends on its intended use, statutory criteria, and technological characteristics. A chatbot used for administrative drafting is not automatically a device, while software that makes a diagnostic or treatment-support claim may require a different regulatory analysis.
FDA’s public figure reported more than 1,600 AI-enabled medical devices authorized for marketing in the United States as of September 2026. That is a point-in-time count of authorized devices, not a count of all clinical AI products and not evidence that any particular product is appropriate for a given patient population.
For a device, ask what intended use and authorization apply, what validation evidence is relevant, how deployment and monitoring are handled, and how modifications are controlled. FDA describes lifecycle considerations that include validation, deployment, monitoring, maintenance, and modification. Those controls complement, but do not replace, HIPAA and organizational privacy review.
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| Situation | Safer decision path |
|---|---|
| A public chatbot receives a pasted clinical vignette containing identifiers | Stop and remove the information. Use only an organization-approved service with a reviewed data flow, or use synthetic or properly de-identified content for the task. |
| An ambient scribe records a visit | Confirm the organization’s policy, patient-facing process where required, vendor role, BAA analysis, recording and transcript retention, access, deletion, and clinician review before filing the note. |
| An EHR assistant retrieves chart context | Review the integration’s permissions, audit trail, subprocessors, reuse and training settings, and the specific contract. Do not assume the EHR connection alone establishes authorization. |
| A model suggests a diagnosis or treatment | Assess intended use and possible FDA device status, define clinician oversight, document validation and monitoring expectations, and apply the same privacy and security review to inputs and outputs. |
| A vendor advertises “HIPAA Certified” or “HIPAA Secure” | Treat the phrase as a claim to verify, not proof. FTC warns against unsupported or misleading HIPAA representations; examine the actual terms, controls, and contractual commitments. |
Plan for incidents, departures, and product changes
Privacy governance continues after launch. Give staff a simple route to report an accidental upload, unexpected disclosure, suspicious account access, or output that contains another patient’s information. Preserve relevant logs and notify the organization’s privacy and security teams promptly so they can assess obligations.
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Review access when clinicians change roles or leave the organization. Remove unused accounts, rotate credentials where required, and confirm that integrations and exports no longer expose data. At scheduled intervals, compare the live configuration with the approved one; a vendor can change retention, subprocessors, model features, or default settings without changing the product name.
For AI-enabled devices, include post-deployment monitoring and change control in the clinical governance process. A modification that changes the intended use or clinical behavior may require a fresh regulatory and privacy assessment.
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What organizations should put in policy
- A list of approved AI tools and configurations, with an owner for each one.
- Permitted purposes and prohibited data types for each tool.
- Rules for PHI, de-identified data, synthetic data, recordings, and patient-facing disclosures.
- Required privacy, security, procurement, and legal reviews, including when a BAA or authorization must be evaluated.
- Retention, deletion, access, audit, incident-reporting, and vendor-change requirements.
- Training for clinicians, contractors, and administrative users.
- Mandatory human review before AI-generated material enters the record or affects care.
- A reassessment trigger for new versions, integrations, subprocessors, model-training terms, or clinical uses.
The AMA’s policy captures the governance principle directly: "Generative AI should: (a) only be used where appropriate policies are in place within the practice or other health care organization to govern its use and help mitigate associated risks; and (b) follow applicable state and federal laws and regulations (e.g., HIPAA-compliant Business Associate Agreement)." Its data-privacy policy also says, "Individuals should know how their data will be used or reused, and the potential risks and benefits."
Limits of a federal U.S. analysis
The HIPAA and FDA points above are federal U.S. guidance. State privacy statutes, state medical-record rules, consent requirements, employment policies, payer contracts, institutional standards, and specialty-specific obligations can add restrictions. The current behavior of an individual model cannot be inferred from a general privacy statement. Verify the exact product version, terms, configuration, contract, and data flow with the organization’s privacy and security personnel before use.
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