--- title: What AI KPIs should I set? description: Setting AI KPIs that link to your AI objectives --- [Skip to content](https://knowledge.adoptech.co.uk/what-ai-kpis-should-i-set#main-content) [![Adoptech-logo-GreyWithoutStrapline-1.png\]](https://knowledge.adoptech.co.uk/hs-fs/hubfs/Adoptech-logo-GreyWithoutStrapline-1.png?height=39&name=Adoptech-logo-GreyWithoutStrapline-1.png)](https://knowledge.adoptech.co.uk/?hsLang=en) Open main navigation Close main navigation Adoptech Help Centre - There are no suggestions because the search field is empty. 1. [Knowledge base](https://knowledge.adoptech.co.uk/?hsLang=en) 2. [Frameworks & Certifications](https://knowledge.adoptech.co.uk/frameworks-certifications?hsLang=en) 3. [ISO 42001](https://knowledge.adoptech.co.uk/frameworks-certifications?hsLang=en#iso-42001) # What AI KPIs should I set? ## Setting AI KPIs that help you measure progress and drive improvement. Key Performance Indicators (KPIs) are measurable values that show how well you are progressing toward your AI Management System (AIMS) objectives. Good KPIs help you understand how effectively your AI Management System is operating, where improvement is needed, and how well AI-related risks are being managed over time. AI KPIs should be relevant to your objectives, measurable, and reviewed as part of ongoing monitoring and management review. ISO/IEC 42001 expects performance evaluation and continual improvement of your AIMS through metrics and evidence (see *Clause 9.1 – Monitoring, measurement, analysis and evaluation* and *Clause 9.3 – Management review*). Below are example AI KPIs you may wish to use or adapt, including a section that shows how KPIs link back to common AI objectives. ### **Examples of AI KPIs** These KPIs provide a high-level view of how effectively the Artificial Intelligence Management System (AIMS) is operating overall. **Number of AI-related incidents** Indicates how often AI systems produce unintended, harmful, or unexpected outcomes. **Number of AI-related non-conformities** Shows how well the organisation complies with its AIMS processes and ISO/IEC 42001 requirements. **Number of stakeholder or customer complaints relating to AI systems** Provides insight into how AI systems are perceived and whether transparency or explainability issues exist. **Percentage of AI systems with a completed and reviewed AI System Impact Assessment** Demonstrates the extent to which AI-related risks and impacts are identified and assessed across AI systems. **Percentage of staff involved in AI activities who have completed required AI training** Helps demonstrate organisational competence and awareness related to responsible AI use. **Number of AI-related supplier or third-party issues identified** Indicates the effectiveness of oversight of AI-related suppliers and dependencies. ### **Examples of KPIs linked to AI objectives** The following examples show how KPIs can be linked to specific AIMS objectives: **Objective: Strengthen AI governance and oversight** **KPI:** Number of AI systems with identified oversight issues during the reporting period **Objective: Improve AI risk assessment coverage** **KPI:** Percentage of AI systems with a completed and reviewed AI System Impact Assessment **Objective: Increase transparency of AI use** **KPI:** Number of stakeholder or user queries, complaints, or challenges relating to AI systems **Objective: Enhance explainability of AI outputs** **KPI:** Number of stakeholder challenges or queries relating to AI decision explainability **Objective: Strengthen AI lifecycle management** **KPI:** Percentage of AI systems reviewed during the reporting period for lifecycle or performance concerns **Objective: Improve monitoring of AI performance and behaviour** **KPI:** Number of AI-related incidents or unintended outcomes identified **Objective: Improve AI incident management** **KPI:** Average time to resolve AI-related incidents **Objective: Increase AI competence and awareness** **KPI:** Percentage of staff involved in AI activities who have completed required AI training. - 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