AI management system objectives
Description
Clause 6.2 — Measurable AIMS objectives consistent with the AI policy; planning to achieve them.
⚠️ Risk Impact
Objectives that aren't measurable produce 'we tried' as the only evidence at audit. Specific objectives enable progress assessment.
🔍 How EchelonGraph Detects This
EchelonGraph's Tier 1 Cloud Scanner automatically checks for this condition across all connected cloud accounts. Violations are flagged as medium-severity findings with remediation guidance.
🔧 Remediation
Set 3-5 AIMS objectives per year with quantitative thresholds: e.g. '% workloads with model card', 'mean time to AI incident response', 'training-data documentation coverage'. Review quarterly.
💀 Real-World Attack Scenario
A consultancy's AIMS objective was 'improve AI governance maturity'. After a year, the team couldn't tell whether they'd improved or not. Auditor: 'How do you know?' — they didn't. Finding: 'inadequate objective measurement'.
💰 Cost of Non-Compliance
Non-measurable objectives: ~45% AIMS implementations fall here (ISO Survey 2024); typical remediation cost: 3-5 days of objective-redesign per cycle.
📋 Audit Questions
- 1.Show me the current AIMS objectives.
- 2.Which were achieved last cycle?
- 3.What was the metric? Show me the data.
- 4.How are objectives chosen — what drives selection?
⚡ Common Pitfalls
- ⛔Qualitative objectives ('improve', 'enhance')
- ⛔Setting objectives at the start of the year and never refreshing
- ⛔Objectives that don't tie to AI policy commitments
📈 Business Value
Measurable AIMS objectives provide leadership-facing progress reporting and audit-defensible evidence of programme effectiveness.
⏱️ Effort Estimate
1-2 days per cycle for objective setting + measurement
EchelonGraph derives AIMS KPI baselines from live workload data; tracks objective progress
🔗 Cross-Framework References
Automate ISO/IEC 42001 42001-6.2 compliance
EchelonGraph continuously monitors this control across all your cloud accounts.
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