Global standard for establishing, implementing, and maintaining an Information Security Management System (ISMS) with AI-specific controls.
Risk-based approach to information security management
Continuous improvement through Plan-Do-Check-Act cycle
Leadership commitment and information security policy
Competence and awareness of personnel handling information
Documented information security controls and procedures
AI Model Access Controls: Implement role-based authentication and authorization mechanisms for AI systems, ensuring only authorized personnel access sensitive models, training data, and deployment configurations per ISO 27001 A.9 requirements.
Continuous Security Monitoring AI: Establish automated monitoring systems to detect anomalies, adversarial attacks, and security incidents affecting AI operations, with documented response procedures aligned to ISO 27001 A.16 incident management standards.
Systematic identification and evaluation of information security risks for AI systems. Annual assessment with quarterly reviews for high-risk systems.
Role-based access controls for AI models, training data, and production systems. Principle of least privilege. Quarterly access reviews.
Classification scheme (Public, Internal, Confidential, Restricted) for AI training data and model outputs. Encryption and access controls per classification.
Formal change approval process for AI model updates, data pipeline changes, and infrastructure modifications. Rollback procedures documented.
Due diligence for third-party AI vendors including security questionnaires, SOC 2 reports, and contractual security requirements.
Change request documentation
Security impact assessment
Testing in non-production environment
Change Advisory Board (CAB) review
Scheduled deployment with rollback plan
Required Roles:
Top-level policy establishing ISMS scope, objectives, and responsibilities. Covers AI systems as critical information assets.
Document listing all ISO 27001 Annex A controls, indicating which are applicable to AI systems and justification for exclusions.
Step-by-step procedures for detecting, responding to, and recovering from security incidents affecting AI systems.
ISO/IEC 27001:2022
Clause 6.1.2: Information security risk assessment process
Annual risk assessments for all AI systems using standardized risk matrix (likelihood x impact). High/critical risks require management approval and mitigation plans.
ISO 27001 Annex A.8.24
Use of cryptography
All AI training data at rest encrypted using AES-256. TLS 1.3 for data in transit. Key management via cloud HSM (AWS KMS, Azure Key Vault).
ISO 27001 Annex A.5.24
Information security incident management planning
Documented incident response procedures. Quarterly tabletop exercises. Incident categorization (P1-P4) with defined SLAs. Post-incident reviews mandatory.
Not legally mandatory, but often required by enterprise customers, regulators (especially in finance/healthcare), and procurement policies. ISO 27001 demonstrates systematic information security management. For AI vendors, certification significantly improves sales win rate (50-70% higher).
Typical timeline: 6-12 months from project start to certification. Includes gap analysis (4-6 weeks), ISMS implementation (3-6 months), internal audits (4-6 weeks), and external certification audit (2-4 weeks). Ongoing surveillance audits annually. For AI-first companies, focus on Annex A controls for cloud, data, and model management.
ISO 27001 is a certification standard (pass/fail against specific controls). SOC 2 is an attestation (auditor reports on controls). ISO 27001 is recognized globally; SOC 2 is primarily North American. For AI companies: pursue SOC 2 for US customers, ISO 27001 for European/APAC customers. Many pursue both.
Explore articles and research about AI governance best practices
Article
A structured checklist for evaluating and approving AI vendors and tools. Covers security, data privacy, compliance, pricing, and enterprise readiness for Malaysia and Singapore companies.
Article
Navigate AI compliance in manufacturing covering predictive maintenance, quality control, worker data protection, and safety regulations across Southeast Asia.
Article
Comprehensive guide to implementing ISO 42001, the world's first AI management system standard. Learn requirements, implementation steps, and certification pathways for responsible AI governance.
Article
Systematic methodology for auditing AI vendor security. Includes assessment framework, comprehensive checklist, and common findings.
We ensure all implementations meet regulatory requirements and industry standards.
Let's discuss how we can help you achieve your AI transformation goals.
Choose your engagement level based on your readiness and ambition
workshop • 1-2 days
Map Your AI Opportunity in 1-2 Days
A structured workshop to identify high-value AI use cases, assess readiness, and create a prioritized roadmap. Perfect for organizations exploring AI adoption. Outputs recommended path: Build Capability (Path A), Custom Solutions (Path B), or Funding First (Path C).
Learn more about Discovery Workshoprollout • 4-12 weeks
Build Internal AI Capability Through Cohort-Based Training
Structured training programs delivered to cohorts of 10-30 participants. Combines workshops, hands-on practice, and peer learning to build lasting capability. Best for middle market companies looking to build internal AI expertise.
Learn more about Training Cohortpilot • 30 days
Prove AI Value with a 30-Day Focused Pilot
Implement and test a specific AI use case in a controlled environment. Measure results, gather feedback, and decide on scaling with data, not guesswork. Optional validation step in Path A (Build Capability). Required proof-of-concept in Path B (Custom Solutions).
Learn more about 30-Day Pilotrollout • 3-6 months
Full-Scale AI Implementation with Ongoing Support
Deploy AI solutions across your organization with comprehensive change management, governance, and performance tracking. We implement alongside your team for sustained success. The natural next step after Training Cohort for middle market companies ready to scale.
Learn more about Implementation Engagementengineering • 3-9 months
Custom AI Solutions Built and Managed for You
We design, develop, and deploy bespoke AI solutions tailored to your unique requirements. Full ownership of code and infrastructure. Best for enterprises with complex needs requiring custom development. Pilot strongly recommended before committing to full build.
Learn more about Custom Buildfunding • 2-4 weeks
Secure Government Subsidies and Funding for Your AI Projects
We help you navigate government training subsidies and funding programs (HRDF, SkillsFuture, Prakerja, CEF/ERB, TVET, etc.) to reduce net cost of AI implementations. After securing funding, we route you to Path A (Build Capability) or Path B (Custom Solutions).
Learn more about Funding Advisoryenablement • Ongoing (monthly)
Ongoing AI Strategy and Optimization Support
Monthly retainer for continuous AI advisory, troubleshooting, strategy refinement, and optimization as your AI maturity grows. All paths (A, B, C) lead here for ongoing support. The retention engine.
Learn more about Advisory Retainer