AI Data Processing Agreements: Where Is Your Business Data Really Being Processed?

TL;DR: AI Data Processing Agreements (DPAs) present growing concerns around where business-critical data is processed and stored. With AI platforms leveraging complex cloud infrastructures, ensuring compliance with GDPR, data residency laws, and contractual controls has become essential. This article explores the key risks and outlines best practices for securing your data in the age of AI.

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AI Data Processing Agreements (DPA): Where Is Your Business Data Really Being Processed?

By Richard Keenlyside Global CIO, Technology Strategist & Transformation Leader

Artificial Intelligence is transforming how businesses operate. From intelligent automation to predictive analytics, AI has become indispensable. But beneath the surface of innovation lies a legal and operational risk often buried in the fine print of AI Data Processing Agreements (DPAs): Where is your data actually being processed?

Why AI Data Residency Matters More Than Ever

As global CIOs and tech leaders, we must recognise that data isn't just a digital asset—it's subject to jurisdictional control. The geographic location where data is processed can determine whether your business is compliant with laws like the General Data Protection Regulation (GDPR), the UK Data Protection Act, or emerging international frameworks such as the EU AI Act.

Many AI providers use cloud infrastructures that route data across regions—sometimes without the customer’s full understanding. As I've seen across industries from manufacturing to retail, this opacity can pose substantial regulatory, security, and reputational risks.

Key Business Concerns in AI DPAs

1. Lack of Data Transparency:AI vendors often fail to specify the exact locations or jurisdictions where data is stored or processed. This opens questions about compliance and control.

2. Subprocessors and Third-Party Access:Many AI platforms rely on subcontractors and subprocessing chains—raising concerns over unauthorised data exposure and contractual accountability.

3. Data Transfer Across Borders:Cross-border data movement without adequate safeguards violates laws like GDPR and exposes businesses to fines and operational disruptions.

4. Model Training and Data Retention:Some DPAs permit AI vendors to use your data to train models unless explicitly restricted. This raises intellectual property (IP) and privacy concerns.

5. Auditing and Termination Rights:Businesses often lack proper audit rights or post-contract data deletion assurances, limiting control once data is in the AI provider’s ecosystem.

   
   

The Compliance Landscape: GDPR, AI Act & Beyond

GDPR mandates that personal data should not be transferred outside the European Economic Area (EEA) without sufficient protection. AI systems must now comply with data localisation requirements and clearly define usage boundaries. The upcoming EU AI Act tightens restrictions further, especially for high-risk AI applications.

A CIO’s Perspective: Strategic Data Governance in AI Contracts

In my work with organisations like LoneStar Group, FitFlop, and MI Dickson, I’ve consistently advocated for AI-readiness frameworks that go beyond technology. Data governance is at the heart of it. AI DPAs must align with your organisation’s wider data strategy—covering data lineage, retention, localisation, and ethical use.

Businesses must proactively review AI DPA clauses that cover:

• Data residency and localisation commitments

• Access control, encryption and sovereignty rights

• Limitation of liability for data misuse

• Subprocessor disclosures and data mapping

• Exit strategies including data portability and deletion

  
  

Best Practices to Mitigate AI Data Risks

• Perform Data Mapping Audits: Know where your data travels—from collection to processing and storage.

• Negotiate Custom DPA Clauses: Don’t rely on generic templates—demand clarity on data handling, location, and usage rights.

• Mandate Local Data Zones: Ensure your data stays within trusted jurisdictions (e.g., UK-only or EU-only zones).

• Disallow Model Training by Default : Explicitly deny the use of your data for vendor model training unless justified and agreed.

• Regular Compliance Reviews: Set up ongoing assessments to check vendor adherence to contractual and legal obligations.

  
  

FAQs

Q1: What is an AI Data Processing Agreement (DPA)? It’s a legal document that defines how an AI vendor will handle, process, store, and protect your data.

Q2: Why is data residency critical in AI contracts? Because legal protection depends on where data is processed—not just how. Different countries have different privacy laws.

Q3: Can I stop an AI provider from using my data for training? Yes. This must be clearly stated in your DPA under “data use” and “training rights.”

Q4: What are the risks of not knowing your data’s location? Non-compliance with GDPR, IP exposure, unauthorised access, and reputational damage.

Q5: Are cloud-based AI tools more vulnerable to data movement? Yes—especially when using hyperscalers with global architectures unless you specify data zones.

Final Word: Take Control Before AI Takes Over

AI is redefining digital transformation—but that doesn’t mean you should sacrifice control over your data. A well-structured AI Data Processing Agreement ensures compliance, builds trust, and protects your business. Before signing, always ask: Where exactly is my data going?

Richard Keenlyside is the Global CIO for the LoneStar Group and a previous IT Director for J Sainsbury’s PLC.