AI System Impact Assessment

ISO/IEC 42005 provides practical guidance for organizations performing artificial intelligence (AI) system impact assessments. It helps organizations developing, providing or using AI systems systematically identify, analyse and address reasonably foreseeable impacts, both beneficial and harmful, on individuals, groups of individuals and societies.

The standard focuses on structured evaluation of how AI systems may impact: People, Business operations, Privacy, Security, Human rights, Society, and Regulatory compliance. It supports seamless integration with AI risk management (ISO/IEC 23894) and AI management systems (ISO/IEC 42001), fostering transparency, trustworthiness and accountability across the AI system lifecycle.

This guidance on AI assessments can be performed through a professional-grade software platform (www.itgovernance.com/pia/) that delivers a structured, auditable and collaborative workflow. Users are guided step-by-step through interactive modules covering system context, stakeholder identification, impact categories, visual risk mapping, controls review, residual impact determination and governance decision-making. The platform generates complete documentation ready for review and approval, with full version control and multi-role collaboration.

Why This Matters

The growing application of AI systems brings significant benefits. At the same time, there are concerns about reasonably foreseeable negative effects, including potentially harmful, unfair or discriminatory outcomes, environmental harm and unwanted reductions in workforce. An AI system can be technically accurate and still create unacceptable impact. Accuracy alone is not enough.

Systematic Assessment Process

The assessment process goes beyond technical testing. Operationalised in a guided digital environment, it includes seven structured steps that ensure impacts are fully considered:

1. 1. Defining AI system context
   Capturing the nature, scope, purpose, intended and unintended uses, data, algorithms, models and deployment environment through interactive description modules.
2. 2. Identifying affected stakeholders
   Systematically identifying individuals, groups of individuals, societies and other interested parties that can be affected, including vulnerable persons, workers and data subjects.
3. 3. Assessing impact categories
   Evaluating impacts across People, Business operations, Privacy, Security, Human rights, Society and Regulatory compliance, using the standard's harms and benefits taxonomy.
4. 4. Evaluating severity & likelihood
   Using visual risk mapping (severity versus likelihood) within the platform to position each identified impact and prioritise attention.
5. 5. Reviewing controls & mitigations
   Assessing existing or planned measures, selecting recommended controls from the knowledge base, and documenting how safeguards address identified harms.
6. 6. Determining residual impact
   Calculating remaining impact after controls, comparing against organisational thresholds for sensitive or restricted uses, and generating residual risk acceptance statements.
7. 7. Governance review & decision making
   Routing the completed assessment through multi-role collaboration (preparer, reviewer, approver) for formal review, approval and continual improvement decisions.

The digital workflow ensures every requirement of the standard is addressed systematically while supporting multi-disciplinary input and generating auditable evidence for conformity assessment and regulatory readiness.

Key Features of the Guided Assessment

• Structured Guided Workflow - Interactive modules covering all seven process steps, from context definition through governance decision-making.
• Visual Risk Mapping - Built-in severity/likelihood visualisation of impacts across the taxonomy of accountability, transparency, fairness, privacy, reliability, safety, explainability and environmental dimensions.
• Automated Traceability & Report Generation - Real-time compliance coverage, automated linking of answers to standard requirements, and one-click generation of complete assessment reports, residual impact statements and action plans.
• Secure Multi-User Collaboration - Role-based access (preparer, reviewer, approver), version history and secure exchange with internal and external parties.
• Extensive Knowledge Base - Curated guidance, recommended controls and best practices aligned with the standard, continuously available within the workflow.
• Lifecycle & Continuous Focus - Built-in support for reassessment triggers, monitoring and closed-loop feedback into design and risk treatment.

Benefits

• Regulatory Confidence - Structured, evidence-based approach that minimises compliance risk and prepares organisations for scrutiny, audits and conformity assessment.
• Beyond Accuracy - Ensures evaluation of Fairness, Explainability, Transparency, Human oversight, Accountability and Societal impact - recognising that technical performance alone is insufficient.
• Efficiency - Reduces manual documentation effort significantly through guided modules, reusable templates and automated outputs.
• Collaboration - Enables seamless multi-disciplinary and multi-stakeholder input with clear roles and approval flows.
• Scalability - Suitable for single systems or enterprise-wide AI portfolios; adaptable to organisations of any size.
• Continuous Governance - Supports the principle that AI Impact Assessment is not a one-time exercise. Assessments are repeated across the AI lifecycle, when models change, when risks evolve, and when business context changes.

Target Users

• Organisations developing, providing or using AI systems (any size or sector)
• AI System Providers, Manufacturers & Deployers
• Quality, Compliance & Risk Managers
• Data Protection, Ethics & Human Rights Officers
• Legal & Regulatory Affairs Teams
• Top Management, Internal Auditors & Governance Bodies
• Consultants, Notified Bodies & Policy Advisors