ISO/IEC 42001 Lead Implementer Training — Lesson 2: AI Risk, Impact Assessment, Objectives, Controls, and Treatment

Learning Objectives

• Interpret the principles, requirements, roles, and dependencies shaping ai risk, impact assessment, objectives, controls, and treatment.
• Apply the workflow and produce AI risk and control treatment register that can withstand review.
• Analyze “a low technical score hides significant human impact” and recommend a proportionate evidence-based response.

Detailed Topics

• AI risk criteria
• impact assessment
• risk identification
• risk analysis
• risk evaluation
• control selection
• risk treatment
• AI objectives
• Competence, communication, governance, documented information, risk, and follow-up

Instructor Demonstration

The instructor demonstrates the ai risk, impact assessment, objectives, controls, and treatment workflow, identifies applicable inputs and responsibilities, records checkpoints in AI risk and control treatment register, and contrasts the accepted state with a condition where a low technical score hides significant human impact.

Hands-On Exercise

Complete a controlled implementation, audit, analysis, or foundation exercise for AI Risk, Impact Assessment, Objectives, Controls, and Treatment. Establish scope and criteria, collect or create evidence, examine “a low technical score hides significant human impact,” reach a supported conclusion, and preserve the result in AI risk and control treatment register.

1. Confirm objectives, scope, roles, criteria, stakeholders, and expected outputs.
2. Perform planned activities while recording assumptions, evidence, and decisions.
3. Test a normal case, an exception, and a follow-up or improvement condition.
4. Document conclusions, owners, due dates, escalation, and verification requirements.

Scenario Analysis

• Identify the requirement or principle with the strongest influence on ai risk, impact assessment, objectives, controls, and treatment.
• Compare two defensible responses and explain governance, risk, and evidence trade-offs.
• Determine how AI risk and control treatment register should be approved, retained, reviewed, and updated.

Troubleshooting Guidance

Separate missing evidence from ineffective practice, and distinguish a documentation issue from a control, process, governance, or competence failure. Use AI risk and control treatment register to trace the earliest divergence. Treat “a low technical score hides significant human impact” as a hypothesis until the response is validated against the relevant requirement and intended outcome.

Validation Checklist

• The scope, criteria, stakeholders, and intended outcome for ai risk, impact assessment, objectives, controls, and treatment are explicit.
• The AI risk and control treatment register links statements and decisions to objective, reviewable support.
• Responsibilities, competence, communication, risk, legal duties, and change impact were considered.
• Findings, corrective actions, monitoring, review triggers, and improvement ownership are clear.

Lesson Outcome

Learners can apply AI Risk, Impact Assessment, Objectives, Controls, and Treatment, explain the reasoning, and defend the result through AI risk and control treatment register.