AI Vendor Data Processing Agreements: What Should Be Included

When you send data to an AI vendor, you remain responsible for protecting that data under privacy laws. A Data Processing Agreement (DPA) establishes the rules. For AI vendors, DPAs need provisions that standard templates don't include.

Executive Summary

• DPAs are legally required when vendors process personal data on your behalf under PDPA
• AI vendors require additional DPA provisions beyond standard data processing
• Key AI-specific concerns: model training, data retention for improvement, cross-border processing
• Standard vendor DPAs often don't adequately protect you—negotiate enhancements
• Sub-processor management is critical as AI vendors use many third-party services
• PDPA (Singapore and Malaysia) requirements should be explicitly addressed
• Don't sign an AI contract without a compliant, comprehensive DPA
• Review DPAs annually as vendor practices and regulations evolve

Why This Matters Now

AI services process data in ways traditional software doesn't:

• Data may train models used by other customers
• Retention periods may extend indefinitely for "improvement"
• Processing often crosses borders through cloud infrastructure
• Sub-processors (cloud providers, model APIs) add complexity

Standard DPAs written for traditional SaaS may not address these concerns. You need AI-specific provisions.

Definitions and Scope

Data Controller: The organization that determines the purposes and means of processing personal data (usually you).

Data Processor: The organization that processes personal data on behalf of the controller (the AI vendor).

Sub-Processor: Third parties engaged by the processor to assist in processing (cloud providers, APIs, etc.).

Data Processing Agreement (DPA): Contract establishing data protection obligations between controller and processor.

Scope of this guide: DPA requirements for commercial AI software/platform vendors processing personal data—not custom development or consulting.

DPA Structure for AI Vendors

Section 1: Scope and Purpose

Standard elements:

• Description of processing activities
• Categories of data subjects
• Types of personal data
• Purpose of processing
• Duration of processing

AI-specific additions:

PROCESSING SCOPE - AI SPECIFIC

AI-Related Processing
In addition to providing the Services, Processor may process 
Personal Data for the following AI-related purposes only with 
Controller's explicit consent:
□ Training machine learning models
□ Improving AI accuracy
□ Benchmarking AI performance
□ Other: [specify]

If no boxes are checked, Processor shall not use Personal Data 
for any AI-related purpose beyond direct service delivery.

Processing Limitations
Personal Data shall not be:
- Used to train AI models for third parties
- Aggregated with other customers' data for model training
- Retained beyond service delivery requirements
- Processed for purposes incompatible with those specified

Section 2: Processor Obligations

Standard obligations:

• Process only on documented instructions
• Ensure personnel confidentiality
• Implement appropriate security measures
• Assist with data subject requests
• Notify breaches
• Submit to audits

AI-specific obligations:

PROCESSOR OBLIGATIONS - AI SPECIFIC

Model Training Controls
Processor shall:
- Maintain technical controls to prevent Personal Data from being 
  used in model training without Controller's consent
- Provide Controller with option to opt out of any collective 
  learning features
- Document any model training using Controller's data

Data Isolation
Processor shall:
- Logically separate Controller's Personal Data from other customers
- Not commingle training data across customer boundaries without consent
- Maintain audit trail of data usage

Algorithmic Transparency
Upon request, Processor shall:
- Explain in plain language how AI processes Personal Data
- Document decision-making logic affecting data subjects
- Provide information sufficient for Controller to respond to 
  data subject inquiries about automated decisions

Section 3: Data Subject Rights Support

Standard requirements:

• Assist Controller with access requests
• Support correction and deletion
• Enable data portability
• Support restriction of processing

AI-specific requirements:

DATA SUBJECT RIGHTS - AI SPECIFIC

Automated Decision-Making
Where AI makes automated decisions affecting data subjects, 
Processor shall:
- Provide meaningful information about the logic involved
- Support data subject requests for human review
- Enable Controller to provide explanations to data subjects

Right to Deletion
Upon deletion request:
- Remove Personal Data from active systems within [X] days
- Remove from backups within [X] days
- Confirm whether data was used for model training
- If used for training, explain impact of deletion (or inability 
  to fully delete from trained models)

Section 4: Security Measures

Standard requirements:

• Encryption
• Access controls
• Vulnerability management
• Incident response

AI-specific additions:

SECURITY - AI SPECIFIC

AI System Security
In addition to standard security measures, Processor shall:
- Protect AI models from adversarial attacks
- Implement input validation to prevent prompt injection
- Monitor for anomalous outputs indicating compromise
- Secure APIs against unauthorized access

Data Protection in AI Context
- Implement differential privacy or similar techniques where appropriate
- Apply data minimization to AI training sets
- Remove or anonymize Personal Data from production AI models 
  where technically feasible

Section 5: Sub-Processors

Standard requirements:

• Prior authorization for sub-processors
• Notification of changes
• Binding contracts with sub-processors
• Processor remains liable for sub-processors

AI-specific requirements:

SUB-PROCESSORS - AI SPECIFIC

AI Infrastructure Disclosure
Processor shall disclose all AI-specific sub-processors including:
- Cloud AI/ML platform providers
- External model API providers
- Data annotation services
- Specialized AI infrastructure

Sub-Processor Assessment
Before engaging AI-specific sub-processors, Processor shall assess:
- Their data handling practices
- Model training policies
- Data residency and transfer practices
- Security certifications

Controller may object to any sub-processor within [X] days of notice.

Section 6: International Transfers

Standard requirements:

• Identify transfer destinations
• Implement appropriate safeguards
• Comply with transfer restrictions

AI-specific considerations:

CROSS-BORDER TRANSFERS - AI SPECIFIC

AI Processing Locations
Personal Data may be processed in the following locations:
[List specific jurisdictions]

Transfer Mechanisms
The following transfer mechanisms apply:
□ Standard contractual clauses
□ Adequacy determination
□ Binding corporate rules
□ Specific consent

Model Training Locations
If permitted, model training may occur in: [specify]
Training data shall not be transferred to jurisdictions beyond 
those specified without Controller's consent.

SINGAPORE/MALAYSIA PDPA
Processor commits that all cross-border transfers comply with:
- Singapore PDPA Section 26 requirements
- Malaysia PDPA Section 129 requirements (if applicable)

Section 7: Data Retention and Deletion

Standard requirements:

• Return or delete data on termination
• Retention period limits
• Secure deletion methods

AI-specific additions:

RETENTION AND DELETION - AI SPECIFIC

Model Training Data
Data used for model training shall be:
- Retained only for documented training purposes
- Deleted or anonymized when no longer needed
- Not retained indefinitely for "potential future use"

Deletion Certification
Upon contract termination, Processor shall certify:
- All Personal Data deleted from production systems
- Backups will be deleted per retention schedule
- Any data used in model training has been [deleted/anonymized/
  remains in trained model weights which cannot be extracted]

Retention Schedule
| Data Category | Retention Period | Justification |
|--------------|------------------|---------------|
| Active service data | During contract | Service delivery |
| Backup data | [X] days post-termination | Business continuity |
| Training data | [specify] | [specify] |
| Logs | [X] months | Security/compliance |

Section 8: Audit and Compliance

Standard requirements:

• Right to audit
• Compliance certification
• Cooperation with regulators

AI-specific additions:

AUDIT AND COMPLIANCE - AI SPECIFIC

AI-Specific Audit Rights
Controller may audit or assess:
- AI model training practices
- Data usage in AI systems
- Algorithmic decision-making processes
- Bias and fairness testing results

Compliance Documentation
Processor shall maintain and provide upon request:
- Records of any Personal Data used for model training
- AI system impact assessments
- Bias/fairness testing documentation
- Model versioning and update records

DPA Review Checklist

AI DPA REVIEW CHECKLIST

Scope
□ All AI processing activities described
□ Model training permissions clearly stated
□ Controller consent requirements for AI use
□ Data categories and subject types specified

Processor Obligations  
□ Model training controls specified
□ Data isolation requirements
□ Transparency obligations
□ Instruction compliance

Data Subject Rights
□ Automated decision-making support
□ Explanation capabilities
□ Deletion impact on models addressed

Security
□ AI-specific security measures
□ Adversarial attack protection
□ Input/output monitoring

Sub-Processors
□ AI infrastructure providers listed
□ Assessment requirements
□ Objection rights

International Transfers
□ Processing locations specified
□ Transfer mechanisms documented
□ PDPA compliance confirmed

Retention and Deletion
□ Training data retention limits
□ Deletion certification process
□ Model impact addressed

Audit
□ AI-specific audit rights
□ Documentation requirements
□ Regulatory cooperation

Common Failure Modes

1. Using Generic DPA

Problem: Standard templates don't address AI-specific concerns Prevention: Add AI-specific provisions per this guide

2. Vague Training Permissions

Problem: Unclear whether vendor can use data for training Prevention: Explicit opt-in/opt-out provisions

3. Ignoring Sub-Processors

Problem: AI vendors use many third-party services Prevention: Require complete sub-processor disclosure

4. Inadequate Deletion Provisions

Problem: Data in trained models can't be fully deleted Prevention: Address this reality explicitly in DPA

5. Missing Transfer Safeguards

Problem: AI processing crosses borders without proper protections Prevention: Specify locations and transfer mechanisms

FAQ

Q: Is a DPA legally required for AI vendors? A: If the vendor processes personal data on your behalf, yes—under PDPA and similar regulations.

Q: Can I use the vendor's standard DPA? A: Review carefully. Vendor DPAs are often minimal. Negotiate AI-specific additions.

Q: What if the vendor won't negotiate DPA terms? A: For significant vendors, this is a red flag. Consider alternatives. Document the gap in your risk assessment.

Q: How do I handle AI vendors that use my data to train models? A: Either prohibit it contractually, or ensure explicit consent with clear limitations.

Q: What about data that can't be fully deleted from trained models? A: Address this honestly in the DPA. Acknowledge limitations and document mitigation.

Disclaimer

This guide provides general information about Data Processing Agreements and is not legal advice. DPA terms should be reviewed by qualified legal counsel and data protection specialists familiar with your jurisdiction.

Next Steps

AI vendors require DPAs with provisions standard templates don't include. Review your existing AI vendor DPAs against this guide and negotiate enhancements where needed.

Need help with AI vendor data protection agreements?

Book an AI Readiness Audit to get expert guidance on vendor compliance and data protection.

References

• Singapore PDPC: "Guide to Data Protection Provisions"
• Malaysia Department of Personal Data Protection: "PDPA Guidelines"
• IAPP: "Data Processing Agreements for AI"
• European Data Protection Board: "Guidelines on Processor Contracts"