The Security Rule applies to covered entities and business associates handling electronic protected health information.
HHS Office for Civil Rights — HIPAA Security Rule · verified 2026-09-22Industry / Healthcare
AI security assessment for Healthcare
Secure AI that touches PHI, healthcare workflows, and the vendor relationships your customers scrutinize.
01 / CONTEXT
AI is entering healthcare workflows faster than the evidence around it.
Healthcare AI can place protected health information inside third-party services, clinical workflows, and vendor platforms. HHS explicitly identifies a third-party AI chatbot that handles patient PHI as an example of a business associate relationship, making data-flow and vendor-boundary review a concrete HIPAA concern.
The HIPAA Security Rule requires regulated entities to protect electronic PHI with administrative, physical, and technical safeguards. AI does not create an exception: when ePHI enters an AI-enabled workflow, the organization still needs an accurate understanding of where that information is created, received, maintained, or transmitted and what safeguards apply.
Ayliea’s healthcare assessment focuses on evidence: AI-system inventory, PHI boundaries, vendor responsibilities, access controls, retention behavior, security configuration, and documented risk treatment. The objective is not to label an AI product 'HIPAA compliant' in isolation, but to evaluate the actual use case and control environment.
02 / Current signals
What shapes the review.
Primary-source requirements and guidance establish the context. The engagement still follows the actual system, data, and use case in scope.
HHS identifies third-party AI chatbots handling patient PHI as an example of a business-associate relationship.
HHS Office for Civil Rights — Business Associates guidance · verified 2026-09-22OCR continues to emphasize accurate and thorough risk analysis as a core HIPAA Security Rule obligation.
HHS Office for Civil Rights — 2026 enforcement guidance · verified 2026-09-2203 / Requirements & frameworks
Map evidence to the environment around the AI.
Frameworks are not treated as interchangeable certifications. Ayliea uses the requirements and guidance that actually belong in the engagement scope.
HIPAA Security Rule
For HIPAA-regulated entities, the Security Rule establishes administrative, physical, and technical safeguards for electronic protected health information. Assessment scope should follow the actual ePHI and system boundaries.
NIST AI RMF
A voluntary cross-sector framework for managing AI risks across governance, mapping, measurement, and management activities.
NIST Generative AI Profile
NIST AI 600-1 supplements the AI RMF with risks and suggested actions specific to generative AI.
Industry requirements
Business-associate responsibilities, contractual requirements, medical-device obligations, and other healthcare requirements depend on the organization, system, data, and use case in scope.
04 / Assessment surface
What we examine in Healthcare.
The exact procedures are scoped to the organization. These are common areas that shape evidence requests and assessor judgment.
PHI & AI Data Boundaries
Map where PHI or other sensitive health information enters AI-enabled products, assistants, agents, APIs, and vendor services; review retention, access, transmission, and approved-use boundaries.
AI Vendor & Business-Associate Risk
Review third-party AI providers and subprocessors that may create, receive, maintain, or transmit PHI, including contractual boundaries, security evidence, configuration assumptions, and responsibility allocation.
Identity, Access & Privileged AI Actions
Assess who can access AI systems and sensitive data, how service accounts and integrations are authenticated, and whether agentic or automated actions have appropriately constrained permissions.
Clinical & Operational Workflow Safeguards
For AI embedded in clinical or healthcare operations, document human review, failure handling, security dependencies, and the controls that prevent an AI output or integration from silently bypassing established workflow safeguards.
Logging, Monitoring & Incident Readiness
Evaluate whether AI activity, access, security-relevant events, and vendor incidents can be detected, investigated, escalated, and connected to the organization’s broader HIPAA security and incident-response processes.
Customer & Reviewer Evidence
For healthcare vendors, assemble defensible evidence about AI architecture, data flows, safeguards, vendor dependencies, limitations, and remediation so hospital or health-system security teams can review the actual environment.
05 / Common review needs
Start with the problem you are actually trying to solve.
These focused pages go deeper on common security and diligence questions in this industry.
01
HIPAA AI Risk Assessment
Assess where AI systems touch ePHI, which vendors and workflows are involved, what safeguards are evidenced, and where the use case creates unresolved security risk.
Explore this review →02AI Vendor Security Assessment for Healthcare
Evaluate the AI-specific evidence a hospital, health system, payer, or other healthcare customer may ask a technology vendor to explain.
Explore this review →06 / OUTPUT
Evidence a reviewer can interrogate.
Ayliea documents the systems reviewed, evidence examined, findings, limitations, framework mappings, remediation priorities, and accountable human review. The report is designed to support diligence and internal risk decisions—not to substitute for legal advice or a regulator’s determination.
ASSESSMENT RECORD
AI system inventory
Data-flow & boundary review
Evidence references
Findings & limitations
Industry-relevant mappings
Remediation priorities
Accountable sign-off
07 / SCOPE THE WORK
Start with the AI system and the evidence you already have.
We will determine whether an independent assessment fits the review, customer, compliance, or security question you need to answer.