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ISO/IEC 27001

Information Security Management

Updated: September 26, 2025 

Overview

ISO/IEC 27001 is an international standard published by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). It defines the requirements for establishing, implementing, maintaining, and continually improving an Information Security Management System (ISMS). It applies to organizations of all sizes and sectors that process, store, or manage sensitive information — including AI developers, SaaS platforms, and healthcare providers handling patient data.

History

  • Origins: First published in 2005 (building on British Standard BS 7799), with major revisions in 2013 and 2022 to reflect evolving cybersecurity risks.
  • Scope: Provides a systematic approach to managing sensitive data through policies, procedures, risk management, and security controls.
  • Annex A controls: In the 2022 revision, Annex A contains 93 controls across areas such as access management, cryptography, operations security, and supplier management (down from 114 in the 2013 version).
  • Certification: Organizations can undergo an accredited external audit to achieve formal ISO/IEC 27001 certification, typically renewed every 3 years with surveillance audits annually.

Why is it relevant

  • Provides a structured framework for protecting health and personal data using internationally recognized standards.
  • Establishes comprehensive administrative, physical, and technical safeguards for information security.
  • Often required in vendor risk management processes and procurement for healthcare and government contracts.
  • Provides a strong baseline that complements HIPAA, SOC 2, and GDPR requirements.

 

Scope of application

ISO/IEC 27001 is widely applied across industries and especially important in healthcare and AI-enabled systems:

  • AI healthcare vendors: Providers of machine learning platforms, model hosting, or analytics handling PHI.
  • Hospitals and insurers: Entities managing electronic health records, claims, and medical imaging systems.
  • Cloud services: Infrastructure and SaaS providers storing or transmitting patient data.
  • Telehealth and digital health platforms: Applications offering virtual care or remote patient monitoring.
  • Third-party processors: Data labeling, IT support, or outsourced services handling healthcare information.

 

Core concepts and requirements

  • Risk assessment and treatment: Identify, evaluate, and treat information security risks systematically.
  • ISMS governance: Define scope, leadership responsibilities, and continual improvement mechanisms.
  • Policies and procedures: Establish documented rules for access control, acceptable use, incident management, and supplier oversight.
  • Annex A control domains (examples):
    • Organizational controls – roles, responsibilities, policies
    • People controls – background checks, training, awareness
    • Physical controls – secure areas, access restrictions, equipment management
    • Technological controls – encryption, logging, system monitoring
  • Incident response: Establish detection, reporting, and response capabilities for security breaches.
  • Audit and monitoring: Conduct internal audits, management reviews, and third-party certification audits.

 

 

 

 

 

How it applies to AI in healthcare

  • Secure model lifecycle: Apply risk-based controls for data collection, training, deployment, and monitoring of AI systems handling PHI.
  • Data protection: Use encryption, access control, and anonymization for training datasets and patient-facing outputs.
  • Operational resilience: Ensure availability of AI-driven systems in clinical workflows through backup, disaster recovery, and redundancy.
  • Vendor management: Assess and monitor third-party MLOps tools, APIs, and hosting providers.
  • Transparency: Maintain documentation on how PHI and sensitive data are processed by AI systems to support audits and regulatory reviews.

Best practices for AI developers and healthcare organizations

  • Adopt a structured risk management process aligned with ISO/IEC 27005.
  • Integrate Privacy by Design and HIPAA safeguards into AI development pipelines.
  • Establish AI review boards or ethics committees for healthcare AI deployment.
  • Perform regular penetration testing and security validation for AI and cloud components.
  • Align with overlapping frameworks: HIPAA Security Rule, SOC 2, ISO/IEC 42001, and FDA SaMD guidance.

Future developments

  • Integration with ISO/IEC 42001 (AI management systems) for AI-specific governance.
  • Updates in the 2022 revision emphasize organizational context, leadership, and supply chain security.
  • Growing demand for ISO 27001 certification in healthcare procurement and cross-border data transfers.

Relevant and overlapping laws and frameworks

  • HIPAA (U.S.): ISO/IEC 27001 provides structured controls that support HIPAA Security Rule compliance.
  • GDPR, PHIPA, PIPEDA: Strengthens privacy protections and data governance obligations.
  • SOC 2: ISO 27001 can serve as a baseline for SOC 2 audit readiness.
  • ISO/IEC 42001: Emerging AI governance standard for managing risks across the AI lifecycle.
  • NIST Cybersecurity Framework: Overlapping approach to risk identification, protection, detection, response, and recovery.

References and official sources

ISO/IEC 27001:2022 — Information security, cybersecurity and privacy protection — Requirements: https://www.iso.org/standard/27001

ISO/IEC 27001:2022 — Information Security Management Systems Practical Guide for SMEs: https://www.iso.org/publication/PUB100484.html

ISO/IEC 27001 — Overview by BSI (British Standards Institution): https://www.bsigroup.com/en-US/products-and-services/standards/iso-iec-27001-information-security-management-system/

ISO/IEC 27001 — Microsoft Compliance offering: https://learn.microsoft.com/en-us/compliance/regulatory/offering-iso-27001