Risk Register – Add Risk

Modified on Tue, 14 Apr at 4:28 PM

Overview 

The Add Risk interface allows users to manually record a new AI-related risk within the system. 

This function is used to capture risks that may not originate directly from assessments but still require formal documentation and governance tracking. 

Manually adding risks helps ensure that potential issues affecting AI reliability, compliance, safety, or performance are recorded and monitored.   

Purpose 

The Add Risk form is used to document risks associated with AI systems or datasets. 

Capturing risks manually ensures the organization maintains a complete and traceable record of identified concerns that may impact AI operations or governance outcomes. 

This supports consistent risk oversight across AI development and deployment activities.   

Fields and Guidance 

risk title 

Enter a clear and concise title describing the risk. 

The title should allow users to quickly understand the nature of the issue. 

risk description 

Provide a detailed explanation of the risk. 

Include context, triggers, or conditions that may influence the likelihood or impact of the risk. 

affected stakeholders 

List the individuals or groups impacted by the risk. 

Examples may include: 

  • customers 
  • employees 
  • partners 

Multiple stakeholders can be entered as comma-separated values. 

mitigation plan 

Describe the actions planned to reduce or eliminate the risk. 

This may include controls, process improvements, or monitoring activities intended to manage risk exposure. 

residual risk owner (optional) 

Assign the individual or role responsible for monitoring the remaining level of risk after mitigation actions have been applied. 

due date (optional) 

Specify the target date for addressing or reviewing the risk. 

This supports tracking and accountability for risk mitigation activities.   

Risk Attributes 

risk type 

Select a predefined category that best represents the nature of the risk. 

Examples may include: 

  • model bias 
  • data privacy 
  • model drift 

likelihood 

Indicate the probability that the risk may occur. 

Example values include: 

  • rare 
  • possible 
  • likely 

impact 

Specify the potential severity of the risk if it occurs. 

Example values include: 

  • low 
  • medium 
  • high 

risk source 

Indicates how the risk was identified. 

Examples include: 

  • manual entry 
  • assessment 

mitigation status 

Track progress of mitigation activities. 

Example statuses include: 

  • not started 
  • in progress 
  • complete 

residual risk level 

Indicates the level of risk remaining after mitigation actions have been considered. 

Example values include: 

  • low 
  • medium 
  • high   

Notes 

  • once submitted, the risk appears in the Risk Register Dashboard and can be accessed through View Actions 
  • risks can be linked to specific AI systems or datasets for full traceability 
  • maintaining documented risk records supports governance, audit, and compliance requirements 

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