AI Risk Assessment Template — Identify and Mitigate AI Risks

Why AI Risk Assessments Are Essential

Every AI tool or application introduces risks that must be identified and managed before deployment. Unlike traditional software, AI systems can produce unpredictable outputs, amplify biases, mishandle sensitive data, and create regulatory exposure — often in ways that are not immediately obvious.

A structured AI risk assessment helps your company evaluate these risks systematically, rather than discovering them after an incident. This template provides a practical framework that any company in Malaysia or Singapore can use, regardless of size or industry.

When to Conduct an AI Risk Assessment

An AI risk assessment should be conducted:

• Before deploying any new AI tool or application
• Before expanding the use of an existing AI tool to new departments or data types
• When an AI vendor releases a significant update or changes their terms of service
• After any AI-related incident or near-miss
• As part of your annual risk review cycle

AI Risk Assessment Template

Section 1: AI System Information

Complete this section to document the basic details of the AI system being assessed.

Field	Details
Assessment date	[DATE]
Assessor(s)	[NAMES AND ROLES]
AI system/tool name	[NAME]
Vendor/provider	[VENDOR NAME]
Version	[VERSION NUMBER]
Intended use case	[DESCRIPTION]
Department(s) affected	[LIST]
Data types involved	[LIST]
Number of users	[ESTIMATED COUNT]
Deployment status	[Planned / Pilot / Production]

Section 2: Risk Categories

Evaluate the AI system against each of the following risk categories. Use the scoring matrix at the end of this section.

2.1 Data Privacy Risk

Risk Factor	Assessment
Does the system process personal data?	Yes / No
Types of personal data involved	[List: names, IC numbers, financial data, health data, etc.]
Where is data stored?	[Country/region]
Is data used for model training?	Yes / No / Unknown
Cross-border data transfer?	Yes / No
PDPA (Malaysia) compliance confirmed?	Yes / No / Not Assessed
PDPA (Singapore) compliance confirmed?	Yes / No / Not Assessed
Data retention period	[Duration or policy reference]
Data deletion capability	Yes / No

Likelihood: [1-5] Impact: [1-5] Risk score: [Likelihood x Impact] Mitigation measures: [Describe]

2.2 Accuracy and Reliability Risk

Risk Factor	Assessment
Can outputs contain factual errors (hallucinations)?	Yes / No
How critical are outputs to business decisions?	Low / Medium / High / Critical
Is human review required before output use?	Always / Sometimes / Never
Has output accuracy been tested?	Yes / No
Accuracy rate in testing	[Percentage or qualitative assessment]
Failure mode if output is incorrect	[Describe potential consequences]

Likelihood: [1-5] Impact: [1-5] Risk score: [Likelihood x Impact] Mitigation measures: [Describe]

2.3 Bias and Fairness Risk

Risk Factor	Assessment
Could outputs affect decisions about individuals?	Yes / No
Use cases involving recruitment, performance, or promotion?	Yes / No
Has the system been tested for demographic bias?	Yes / No
Are outputs reviewed for discriminatory content?	Always / Sometimes / Never
Can users provide feedback on biased outputs?	Yes / No

Likelihood: [1-5] Impact: [1-5] Risk score: [Likelihood x Impact] Mitigation measures: [Describe]

2.4 Security Risk

Risk Factor	Assessment
Authentication method	[SSO / Username-password / API key / Other]
Encryption in transit?	Yes / No
Encryption at rest?	Yes / No
Access controls/RBAC?	Yes / No
Audit logging available?	Yes / No
Vendor security certifications	[SOC 2, ISO 27001, etc.]
Penetration testing conducted?	Yes / No / By vendor only
Integration with company systems	[List integrations]

Likelihood: [1-5] Impact: [1-5] Risk score: [Likelihood x Impact] Mitigation measures: [Describe]

2.5 Regulatory and Legal Risk

Risk Factor	Assessment
Industry-specific AI regulations applicable?	Yes / No
MAS guidelines applicable? (Singapore financial services)	Yes / No
BNM guidelines applicable? (Malaysia financial services)	Yes / No
PDPC guidance applicable? (Singapore)	Yes / No
Intellectual property risks identified?	Yes / No
Contractual obligations with clients re: AI use?	Yes / No
Insurance coverage for AI-related claims?	Yes / No

Likelihood: [1-5] Impact: [1-5] Risk score: [Likelihood x Impact] Mitigation measures: [Describe]

2.6 Operational and Dependency Risk

Risk Factor	Assessment
What happens if the AI system is unavailable?	[Describe impact and workaround]
Vendor lock-in risk	Low / Medium / High
Alternative tools available?	Yes / No
SLA with vendor	[Uptime guarantee and support level]
Cost predictability	Fixed / Usage-based / Uncertain

Likelihood: [1-5] Impact: [1-5] Risk score: [Likelihood x Impact] Mitigation measures: [Describe]

Section 3: Risk Scoring Matrix

Score	Likelihood	Impact
1	Rare	Negligible
2	Unlikely	Minor
3	Possible	Moderate
4	Likely	Major
5	Almost certain	Severe

Risk rating:

Combined Score (L x I)	Rating	Action Required
1-4	Low	Accept with monitoring
5-9	Medium	Mitigate and monitor
10-15	High	Mitigate before deployment
16-25	Critical	Do not deploy without executive approval and significant mitigation

Section 4: Overall Assessment Summary

Risk Category	Score	Rating	Key Mitigation
Data Privacy	[X]	[Rating]	[Summary]
Accuracy/Reliability	[X]	[Rating]	[Summary]
Bias/Fairness	[X]	[Rating]	[Summary]
Security	[X]	[Rating]	[Summary]
Regulatory/Legal	[X]	[Rating]	[Summary]
Operational/Dependency	[X]	[Rating]	[Summary]
Overall	[Max]	[Highest]	[Primary action]

Section 5: Approval

Role	Name	Decision	Date
Assessor	[Name]	Assessed	[Date]
Risk Owner	[Name]	Approved / Rejected / Conditional	[Date]
CISO/DPO	[Name]	Approved / Rejected / Conditional	[Date]
Business Sponsor	[Name]	Approved / Rejected / Conditional	[Date]

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How to Use This Template

For First-Time Assessments

Work through every section thoroughly. The first assessment establishes your baseline understanding of the risks and sets the mitigation plan.

For Reassessments

Focus on what has changed since the last assessment — new data types, new users, vendor updates, or incidents. Update scores and mitigation measures accordingly.

Integration with Existing Risk Processes

This AI risk assessment should feed into your company's broader enterprise risk management framework. AI risks should be reported alongside operational, financial, and compliance risks to provide a complete picture for leadership.

Regulatory Alignment

Singapore

This template aligns with the PDPC's AI Governance Framework guidance on risk assessment, as well as MAS guidelines on technology risk management (MAS TRM) for financial institutions.

Malaysia

This template supports compliance with Malaysia's PDPA requirements around data processing impact assessment and Bank Negara Malaysia's risk management expectations for technology adoption.

Related Reading

• AI Policy Template — Build your policy framework around identified risks
• AI Evaluation Framework — Measure quality, risk, and ROI of AI implementations
• Copilot Governance & Access — Apply risk assessment to Microsoft Copilot deployment