Responsible artificial intelligence
Artificial Intelligence Management System (AIMS).
We help organizations adopt artificial intelligence responsibly, transparently and auditably through an Artificial Intelligence Management System aligned with ISO/IEC 42001, which governs the life cycle of AI systems, assesses their impacts and establishes the controls demanded by regulators, customers and society.
What it includes
AIMS assessment and scope
Inventory of AI systems and use cases (developed, acquired or third-party), organizational roles (provider, user, developer), context, interested parties and an AI policy approved by top management.
Governance and responsibilities
AI governance structure, committee, roles and competences, responsible-use principles (transparency, fairness, safety, privacy, human oversight) and internal normative framework.
AI risk and impact assessment
Risk assessment methodology aligned with ISO/IEC 23894 and impact assessment on individuals, groups and society (ISO/IEC 42005), with acceptance criteria and a treatment plan.
Life cycle controls
Implementation of ISO/IEC 42001 Annex A controls: data, development, verification and validation, deployment, operation, monitoring, event logging and retirement of AI systems.
Transparency, use and third parties
Technical and user documentation, communication to interested parties, management of AI model and service providers, and alignment with ISO/IEC 27001 and ISO/IEC 27701 when personal data is processed.
Audit, certification and improvement
Indicators, internal audit, management review, preparation for the ISO/IEC 42001 certification audit and a maintenance program for technological and regulatory change.
Responsible adoption methodology
A continual improvement cycle that integrates the AIMS with existing information security, privacy and continuity systems.
1. Discover
AI inventory, roles, context and policy.
2. Assess
Risks and impacts per system and use case.
3. Control
Life cycle and data controls.
4. Operate
Monitoring, incidents and transparency.
5. Certify
Internal and external audit and continual improvement.
Outcomes for the organization
Governed AI
Adoption decisions with clear owners, risk criteria and human oversight.
Trust and compliance
Auditable evidence for customers, regulators and international AI frameworks.
Sustainable innovation
A controlled life cycle that scales use cases without compromising security or privacy.
Reference frameworks and requirements
- ISO/IEC 42001
- ISO/IEC 42005 (impact)
- ISO/IEC 23894 (AI risk)
- ISO/IEC 22989 and 23053
- NIST AI RMF 1.0
- European Union AI Act
- OECD AI principles
- ISO/IEC 27001 and 27701
Related services
Information security (ISMS)
ISO/IEC 27001: governance, risk, controls and certification.
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Analytics, Big Data, machine learning and ISO/IEC 42001 AI governance.
See service →Executive development and certification
CertiProf Platinum Partner: 57 certifications with a Credly badge.
See service →Shall we talk?
A managing partner will attend you personally. Free 30-minute executive assessment, in person or online.