Why Do AI Services Require Data Processing Agreements?
AI companies providing services that process customer data on behalf of clients must establish Data Processing Agreements (DPAs) or Data Processing Addenda meeting requirements under GDPR, CCPA, and other privacy regulations. These agreements define the legal relationship between data controllers (customers who determine processing purposes) and data processors (AI service providers who process data on controllers’ instructions).
For AI platforms offering services like natural language processing, computer vision, predictive analytics, or custom model training on customer datasets, DPAs are legally required contracts protecting both parties. They clarify each party’s privacy obligations, limit liability exposure, enable regulatory compliance, and provide contractual protections supporting business relationships.
Without proper DPAs, AI companies face regulatory violations and penalties, customer contract breaches, inability to serve enterprise clients requiring compliance, and exposure to liability for data incidents. Understanding what DPAs must contain and how to structure processor relationships is essential for AI service providers processing customer data.
GDPR Requirements for Processor Agreements
Mandatory DPA Elements Under Article 28
GDPR Article 28 requires written contracts between controllers and processors containing specific terms. Required provisions include the subject matter and duration of processing, the nature and purpose of processing, the type of personal data and categories of data subjects, and the controller’s obligations and rights.
The processor must only process data on documented instructions from the controller, ensure personnel are bound by confidentiality, implement appropriate security measures, engage sub-processors only with controller authorization, assist the controller in responding to data subject rights requests, assist with security incidents and breach notifications, delete or return data at the end of services, and make available information demonstrating GDPR compliance.
International Data Transfer Provisions
When processing involves transferring personal data outside the EEA, DPAs must incorporate approved transfer mechanisms. Standard Contractual Clauses (SCCs) are the most common mechanism, containing detailed obligations for data exporters and importers.
The European Commission updated SCCs in 2021 to address concerns raised in the Schrems II decision. AI companies transferring data to the U.S. or other countries must use the new SCCs and conduct Transfer Impact Assessments evaluating whether local laws undermine protections.
Sub-Processor Management
AI services often use sub-processors for infrastructure, specialized processing, or support services. DPAs must address how sub-processors are authorized, either through specific authorization for named sub-processors or general authorization with notification requirements for changes.
Controllers must have the right to object to new sub-processors. Processors remain liable for sub-processor compliance, requiring flow-down obligations in sub-processor agreements.
Security and Technical Measures
Appropriate Security Requirements
DPAs should specify security measures protecting personal data, though specific requirements depend on risk levels and data sensitivity. Common provisions address encryption in transit and at rest, access controls and authentication, logging and monitoring, incident response procedures, and regular security testing and updates.
For AI services, security considerations include protecting training data, securing model endpoints, preventing unauthorized model access, and safeguarding customer-specific models or fine-tuned systems.
Security Incident and Breach Notification
Processors must notify controllers of personal data breaches without undue delay, typically within 24-72 hours. Notification should include the nature of the breach, categories and approximate numbers of affected individuals and records, likely consequences, and measures taken or proposed to address the breach.
Controllers then assess whether to notify supervisory authorities and affected individuals as GDPR requires.
Data Subject Rights Assistance
Supporting Controller Obligations
Controllers must respond to data subject requests exercising rights to access, rectification, erasure, restriction, portability, and objection. Processors must assist controllers in fulfilling these obligations.
DPAs should specify how the processor will provide assistance, response timeframes for assistance requests, any fees for extensive assistance, and technical capabilities supporting rights responses.
Challenges for AI Systems
AI systems create unique challenges for data subject rights. The right to erasure is particularly difficult when personal data is embedded in trained model weights. Processors should be transparent about technical limitations, offering alternatives like restricting future use or retraining models without the data when feasible.
Audit Rights and Compliance Verification
Controller Audit Provisions
GDPR requires processors to make available information demonstrating compliance and allow audits. DPAs should define audit scope and frequency, notice requirements, auditor qualifications, confidentiality protections, and responsibility for audit costs.
Many processors offer alternatives to direct audits, including providing third-party audit reports and certifications (SOC 2, ISO 27001), completing security questionnaires, and allowing limited inspections with reasonable notice.
Certifications and Attestations
AI companies can reduce audit burdens by obtaining recognized certifications demonstrating security and privacy compliance. SOC 2 Type II reports verify security controls, ISO 27001 certification shows information security management, and Privacy Shield successor frameworks (where applicable) support international transfers.
Sharing these attestations with customers often satisfies audit requirements without individual customer audits.
Data Retention and Deletion
End of Service Obligations
DPAs must address what happens to personal data when services end. Typical provisions require deletion or return of all personal data within specified timeframes, certification of deletion upon request, and exceptions for legally required retention.
For AI services, consider whether trained models must be deleted if they contain customer data, how customer-specific configurations or fine-tunings are handled, and retention for backup or archival purposes.
Backup and Archival Data
While processors must delete data, some backups may exist temporarily. DPAs should acknowledge backup retention periods, commit to deletion from backups according to backup rotation schedules, and restrict backup data use to recovery purposes only.
Liability and Indemnification
Allocation of Data Protection Liability
Under GDPR, both controllers and processors can be liable for violations. DPAs should clarify each party’s liability for their respective obligations, indemnification for breaches of DPA terms, and liability caps or exclusions.
Processors typically limit liability to amounts under main service contracts while accepting responsibility for processor-specific obligations like security and sub-processor management.
Insurance Requirements
Enterprise DPAs may require processors to maintain cyber liability and errors and omissions insurance covering data breaches and privacy violations. Specify required coverage amounts, proof of insurance requirements, and notification if coverage lapses.
CCPA and U.S. State Privacy Law Requirements
Service Provider Agreements
CCPA requires written contracts when businesses engage service providers to process personal information. Contracts must prohibit the service provider from retaining, using, or disclosing personal information for any purpose other than performing services, selling or sharing personal information, and combining personal information with information received from other sources.
Service providers must certify they understand and will comply with restrictions.
Differences from GDPR DPAs
While GDPR and CCPA processor agreements serve similar purposes, key differences include CCPA focusing more on sale/sharing restrictions than security details, less prescriptive security requirements in CCPA, and different breach notification timelines and obligations.
Many companies use unified DPAs covering both GDPR and CCPA requirements.
AI-Specific Considerations
Training Data Usage Restrictions
Enterprise customers often prohibit using their data to train general-purpose models that benefit other customers. DPAs should clarify whether customer data will be used for model training, specify that training (if permitted) only improves customer-specific models, prohibit using data to benefit competitors, and describe data isolation and model segregation practices.
Model Output Ownership
Address who owns AI-generated outputs from processing customer data. Typically, customers own outputs generated from their data, but processors may retain rights to learn from aggregated, anonymized usage patterns.
Explainability and Transparency
For AI services making automated decisions about individuals, DPAs may include provisions requiring processors to provide information about decision logic, supporting controllers’ transparency obligations to data subjects.
Template vs. Negotiated DPAs
Standard DPA Approaches
Many AI providers offer standard DPAs that customers can execute without negotiation. Benefits include efficient onboarding, consistent terms across customers, and legal certainty about obligations. Standard DPAs should meet baseline regulatory requirements and be readily available to customers.
Enterprise Negotiation Points
Large customers often negotiate DPA terms. Common negotiation points include expanded audit rights, specific security commitments, customized sub-processor approval processes, enhanced breach notification requirements, and higher liability caps for data protection violations.
Balance customer demands against operational feasibility and risk tolerance.
Updating DPAs for Regulatory Changes
Privacy regulations evolve continuously. Build DPA update mechanisms allowing amendment to comply with new laws, notification processes for material changes, and customer acceptance requirements for updated terms.
Consider whether updates can be made unilaterally or require customer consent, particularly for material changes affecting customer obligations or rights.
Conclusion: Protecting Both Parties Through Comprehensive DPAs
Data Processing Agreements are mandatory legal requirements for AI companies processing customer data and critical business protections clarifying obligations and limiting liability. Effective DPAs address GDPR Article 28 requirements, international data transfers, security measures and breach notification, data subject rights assistance, and AI-specific concerns about training data and model outputs.
Well-drafted DPAs enable AI companies to serve enterprise customers compliantly while managing privacy risks appropriately.
Contact Rock LAW PLLC for DPA Drafting and Privacy Compliance
At Rock LAW PLLC, we help AI companies draft and negotiate Data Processing Agreements meeting regulatory requirements.
We assist with:
- DPA template development for standard customer agreements
- Enterprise DPA negotiation support
- GDPR and CCPA compliance counseling
- Standard Contractual Clauses implementation
- Sub-processor management frameworks
- Privacy program development
Contact us to develop DPAs protecting your AI business while meeting customer compliance needs.
Related Articles:
- Privacy Laws and AI Training on Customer Data
- International AI Regulations Compliance
- Key Contract Provisions for SaaS and AI Agreements
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