Where Does AI Inference Actually Run?

AI inference happens somewhere physical. That location determines which laws govern your data, which courts have jurisdiction, and which governments can compel disclosure. For Canadian organizations subject to PIPEDA Principle 4.1.3 (accountability), Law 25 Section 17 (cross-border transfers), or sector-specific regulations, understanding where inference actually occurs carries real penalties and legal exposure.

Most AI vendors obscure this reality behind marketing terms like "secure cloud infrastructure" or "enterprise-grade encryption." The technical truth is simpler and more consequential than vendor messaging suggests.

---

The inference location problem

When you send a prompt to an AI system, that data travels to wherever the inference engine runs. This isn't just about storage—it's about active processing under foreign jurisdiction.

Large language models require significant computational resources. GPU clusters, memory allocation, and model weights must all exist in a specific physical location. That location determines legal jurisdiction, regardless of where your organization or the vendor's headquarters are located.

Under PIPEDA Principle 4.1.3, Canadian organizations remain accountable for personal information protection even when processed by third parties. This accountability extends to AI inference location and the jurisdictional risks created by foreign processing infrastructure.

Most commercial AI platforms—including OpenAI's GPT models, Anthropic's Claude, and Google's Gemini—run inference on US infrastructure. When Canadian data enters these systems for processing, it becomes subject to US legal frameworks, intelligence gathering, and compelled disclosure requirements.

---

Why encryption doesn't solve jurisdiction

Encryption protects data in transit and at rest. It doesn't protect data during inference, because the model needs access to unencrypted content to process and respond to your prompts.

During inference, your data exists in clear text within the system's memory. GPU processing requires direct access to prompt content, context, and any retrieved documents. Encryption keys must be available to decrypt this information for processing.

This creates a fundamental exposure window. US authorities can compel disclosure of decryption keys, active memory contents, or processed data under various legal frameworks including the CLOUD Act, FISA Section 702, and national security letters.

Law 25 Section 17 requires organizations to evaluate whether foreign jurisdictions provide adequate protection levels. US infrastructure fails this adequacy test due to surveillance authorities including the CLOUD Act, which grants extraterritorial data access powers that contradict Quebec privacy protections.

Encryption at rest is a security control, not a jurisdictional shield. Data must be decrypted for AI inference, creating exposure to foreign legal processes regardless of encryption strength.

---

CLOUD Act implications for Canadian data

The CLOUD Act (Clarifying Lawful Overseas Use of Data Act) allows US authorities to compel US companies to produce data regardless of where it's stored or processed. This includes subsidiaries, partners, and service providers under US corporate control.

For AI inference, this means:

• Prompts containing personal information become subject to US legal processes • Retrieved documents from knowledge bases can be compelled for disclosure
• Conversation histories and derived insights fall under US jurisdiction • Corporate communications processed through AI assistants lose Canadian legal protections

PIPEDA's accountability principle under Principle 4.1.3 makes Canadian organizations responsible for protecting personal information throughout the entire processing lifecycle. Using US-based AI inference creates potential violations regardless of vendor security certifications or contractual protections.

The Privacy Commissioner of Canada has issued guidance stating that "the organization remains accountable for the personal information even when it is being processed by a third party." This accountability extends to inference location and jurisdictional exposure.

---

Regulatory compliance requirements

Canadian privacy regulations impose specific obligations for cross-border data processing that apply directly to AI inference location.

PIPEDA Requirements (Federal): • Principle 4.1.3 requires accountability for all personal information processing • Cross-border transfers must provide comparable protection levels • Organizations must document and justify processing location decisions

Law 25 Obligations (Quebec): • Section 17 mandates adequate protection for information leaving Quebec • Section 89 requires Privacy Impact Assessments for systematic profiling via AI • Section 91 penalties reach 4% of worldwide revenue or C$25 million for serious breaches

Provincial and sector-specific requirements: • Cyber Security and Critical System Protection Act (CSCPA) for federally regulated critical infrastructure • Personal Health Information Protection Act (PHIPA) obligations for healthcare data in Ontario • Financial sector guidelines from OSFI regarding third-party risk management

These requirements apply regardless of vendor promises, contractual terms, or security certifications. Compliance depends on actual infrastructure location and applicable legal frameworks, not vendor marketing claims.

---

How to verify inference location

Due diligence requires concrete verification of where AI inference actually occurs. Marketing materials and sales presentations don't constitute adequate documentation for regulatory compliance.

Infrastructure attestations: Request detailed infrastructure documentation showing physical server locations, data center facilities, and network routing for inference traffic. Look for third-party audits that specifically address processing location, not just storage.

Data processing agreements: Review contracts for specific commitments about inference location. Generic privacy clauses or references to "global infrastructure" don't satisfy Canadian regulatory requirements for cross-border processing documentation under PIPEDA Principle 4.1.3 or Law 25 Section 17.

Third-party dependencies: Understand the complete technology stack. Many AI platforms rely on cloud providers, CDNs, or specialized inference services that may process data in different jurisdictions than the primary vendor suggests.

Regulatory compliance documentation: Ask for specific attestations about PIPEDA compliance, Law 25 conformity, and freedom from CLOUD Act exposure. Generic SOC 2 or ISO 27001 certifications don't address jurisdictional compliance requirements.

---

Canadian AI infrastructure alternatives

Sovereign AI platforms specifically address inference location requirements by running all processing on Canadian infrastructure under Canadian legal jurisdiction.

Augure operates exclusively on Canadian infrastructure with no US corporate parent, investors, or CLOUD Act exposure. Both Ossington 3 and Tofino 2.5 models process all inference requests within Canadian data centers, ensuring compliance with PIPEDA Principle 4.1.3, Law 25 Section 17, and CSCPA requirements.

This architecture provides several compliance advantages:

• All personal information remains under Canadian legal protection throughout the inference process • No exposure to US surveillance authorities or compelled disclosure requirements
• Direct compliance with cross-border processing restrictions in Law 25 and PIPEDA • Simplified regulatory documentation and Privacy Impact Assessment requirements under Law 25 Section 89

Canadian AI infrastructure isn't just about data residency—it's about ensuring all processing, inference, and derived insights remain under Canadian legal jurisdiction throughout the entire AI interaction lifecycle.

For organizations in regulated sectors, sovereign infrastructure eliminates the complex legal analysis required to justify foreign processing under Canadian privacy regulations.

---

Making informed decisions

AI inference location directly impacts regulatory compliance, legal exposure, and operational risk. Organizations subject to Canadian privacy regulations should evaluate AI platforms based on actual infrastructure jurisdiction, not vendor promises or security certifications.

Understanding where inference occurs, which laws apply, and what disclosure requirements exist provides the foundation for informed technology decisions that align with Canadian regulatory obligations including PIPEDA accountability principles and Law 25 cross-border transfer requirements.

For detailed information about sovereign AI infrastructure designed for Canadian regulatory requirements, visit augureai.ca to explore how Canadian-hosted inference supports your compliance objectives.