Assess AI System Risk
Learn how to assess, score, and manage AI system risk in Sprinto using configurable AI risk factors and automated risk scoring workflows.
The AI Systems module in Sprinto includes AI-specific risk assessment workflows that help organisations evaluate the governance, operational, and compliance risks associated with AI systems.
Risk assessments help organisations:
Evaluate AI-related risk exposure
Classify AI systems by risk level
Maintain governance records
Support AI compliance workflows
Prioritise reviews and remediation
Maintain periodic risk reviews
Sprinto supports configurable AI risk scoring workflows aligned with evolving AI governance requirements.
Navigate to the Risk Score Tab
To access AI system risk scoring:
Log in to the Sprinto dashboard.
Navigate to Data Library.
Select AI Systems.
Open an AI system from the Added AI Systems tab.
Select the Risk score tab.
The Risk score tab displays all configured AI risk factors and associated scoring values.
How AI Risk Scoring Works
Sprinto evaluates AI system risk using configurable risk factors.
Each risk factor contains:
Multiple scoring options
Configurable score values
Risk contribution logic
As users select values for risk factors, Sprinto automatically:
Calculates cumulative risk scores
Assigns risk levels
Updates governance posture across the AI inventory
AI Risk Factors
Risk factors help organisations evaluate the impact and governance posture of AI systems.
Depending on your configuration, risk factors may evaluate:
Operational scale
Deployment exposure
Data sensitivity
Decision reversibility
Affected user groups
AI output usage
Business criticality
Regulatory impact
Safety-related usage
Risk scoring workflows can be customised from the Configuration tab.
Add Risk Factor Values
To assess AI system risk:
Open the AI system.
Navigate to the Risk score tab.
Click Add value beside a risk factor.
This opens the risk scoring drawer.
Score AI Risk Factors
Inside the risk scoring drawer:
Expand each risk factor section.
Review the available scoring values.
Select the appropriate value.
Repeat the process for all mandatory risk factors.
Sprinto displays scoring values as selectable options for each factor.
Mandatory Risk Factors
Some risk factors may be marked as mandatory.
The Save changes button remains disabled until:
All mandatory risk factors are scored
Required selections are completed
This helps organisations maintain consistent risk assessments.
Save AI Risk Scores
After completing the assessment:
Click Save changes.
Sprinto:
Saves the selected values
Calculates cumulative risk scores
Updates the AI system risk posture
Displays updated scores in the Risk score tab
Review Risk Scores
After saving, the Risk score tab displays:
Risk factor values
Assigned scores
Calculated risk levels
This helps organisations review how individual risk factors contribute to the overall AI risk posture.
Edit Risk Scores
To update existing risk scores:
Navigate to the Risk score tab.
Click the edit icon beside the risk factor value.
Update the required scoring values.
Click Save changes.
Sprinto recalculates the AI system risk score automatically.
AI Risk Levels
Sprinto supports configurable AI risk levels.
Depending on your configuration, risk levels may include:
No risk
Low risk
Medium risk
High risk
Critical risk
Risk levels are automatically assigned based on configured score thresholds.
Risk Scoring Configuration
AI risk scoring workflows are configurable from the Configuration tab.
Administrators can customise:
Risk factors
Risk factor values
Score thresholds
Mandatory scoring requirements
Risk level ranges
This helps organisations align AI governance workflows with internal risk policies.
Example AI Risk Dimensions
AI risk assessments may include factors such as:
Data Privacy
Evaluates how AI systems handle sensitive or personal data.
Examples include:
PII handling
PHI exposure
Data retention practices
Training data usage
Operational Scale
Evaluates the deployment scale of the AI system.
Examples include:
Internal team usage
Organisation-wide deployment
Public-facing deployment
Population-scale usage
Business Criticality
Evaluates the operational importance of the AI system.
Examples include:
Customer-facing workflows
Revenue-impacting systems
Internal automation tools
Low-impact support systems
Decision Impact
Evaluates how AI outputs influence users or business decisions.
Examples include:
Human-reviewed recommendations
Automated decisions
Access control decisions
Safety-related outcomes
AI Governance Best Practices
When assessing AI system risk:
Review risk assessments periodically
Include compliance and security stakeholders
Evaluate sensitive data exposure carefully
Document business-critical AI usage
Reassess risk after major system changes
Align scoring criteria with governance requirements
Maintain evidence for audit reviews
Relationship Between Risk and Due Diligence
Risk scoring helps organisations determine:
Whether additional due diligence is required
Which AI systems require governance reviews
Which systems need periodic reassessment
Which systems may require remediation activities
Higher-risk AI systems may require:
Additional document collection
Security questionnaires
Governance reviews
Management approvals
Monitoring AI Risk Workflows
Sprinto supports governance monitoring workflows related to AI risk.
Examples include:
AI system risk should be scored
Periodic risk assessment reviews
Management review workflows
Risk reassessment monitoring
These workflows help organisations maintain ongoing AI governance oversight.
Related Information
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