AI in Canada: Legal risk, sovereignty, and why Cohere matters
Artificial intelligence in Canada is being pushed by business ambition, regulatory uncertainty, and a need for technological sovereignty. Cohere sits at the center of that push, as the country's leading foundational model developer focused on enterprise use. Legal and business stakes are rising as quickly as the tech.
Canadian companies, governments, and international partners want options beyond US-based providers. Cohere is the only Canadian player operating at this scale, and that matters for procurement, compliance, and policy.
Why enterprises want a Canadian LLM
"There's really been an impetus for Canadian companies, governments, as well as companies internationally, like in the UK and Europe, to look outside the US for partners in this space," says Kosta Starostin, general counsel at Cohere. The company builds for business workflows, not consumer chatbots, with models meant to integrate into products and processes.
For buyers, legal risk shows up first. Business leaders need clarity on what a foundational model does, what it can't do, and how to move from proof of concept to measurable ROI.
For legal teams, risk comes first
Executives want to future-proof decisions in an area that's new to most organizations. Your job is to translate uncertainty into contracts, policies, and governance that are clear, enforceable, and practical.
- Data use and improvement rights: Will the provider use your inputs, outputs, or metadata to train or improve models? Are there default opt-outs? Is fine-tuning segregated?
- Retention and deletion: How long are logs kept? Can you set retention? Is verified deletion available at termination?
- Security and privacy: Encryption standards, key management, SOC 2/ISO status, access controls, incident response, and breach notification timelines.
- Provenance: What's the position on training data sources, licenses, and removal processes? Are there source categories the provider excludes?
- Testing and evaluation: How are safety, hallucinations, and bias measured? Are eval reports and red-team findings available?
- Jurisdiction and residency: Where is data processed and stored? Is data residency guaranteed by contract?
- Regulatory fit: Does the intended use align with emerging AI rules in your operating regions?
Technical commitment your contracts must reflect
Integrating large models takes serious time, resources, and skilled engineering. Early adopters must justify spend to boards without certainty on outcomes.
- SLAs and SLOs: Latency, uptime, throughput, rate limits, and degradation rules.
- Deployment model: Dedicated VPC, on-premise, or managed service. Who controls keys, logs, and observability?
- Security schedule: Pen-testing, vulnerability disclosure, audit rights, and evidence requests.
- DPA and transfer tools: SCCs/ITRs, PIPEDA/Quebec 25 compliance, and DPIA requirements.
- Rollout plan: Staged POCs, go/no-go gates, evaluation criteria, and acceptance testing.
Data security and provenance under the microscope
Cohere offers deployment models that keep customer data isolated through virtual private cloud or on-premise services. "It's all within the ecosystem of the company; they control everything," Starostin says. The company never sees the data in those configurations.
For counsel, that setup reduces exposure and simplifies data mapping. Pair it with clear provenance positions, content filters, monitoring, and an incident playbook that your security team trusts.
Regulation is moving; build on principles
The rules are still being written across major markets. In the EU, the AI Act sets risk-based obligations and documentation requirements. In Canada, AIDA (part of Bill C-27) frames duties for "high-impact" systems.
Cohere's approach: "security by design" and "privacy by design" built into process. That's the right anchor while details settle. Link your governance to those principles so your policies age well.
B2B vs B2C matters for rulemaking
"We're very squarely in the B2B camp," Starostin says. The concern is getting lumped into consumer frameworks that don't fit enterprise controls and deployment realities.
Document the distinction in your use cases: user access, human-in-the-loop, data flows, and downstream risk. That record helps with regulators and audits.
Sovereignty is now a procurement requirement
Governments in Canada and the UK want data and AI sovereignty. Cohere's deal with the Canadian government to build domestic data and compute centers reflects this push. "They view it as a critical national security asset and interest," Starostin says.
For public sector and regulated buyers, expect localization clauses, residency attestations, and facility audits to become standard.
Practical playbook for in-house counsel
- Vendor diligence: Security attestations, red-team summaries, model cards, eval results, and provenance statements.
- Deployment decision: Default to VPC or on-prem for sensitive data; restrict model improvement rights by contract.
- DPIA/PIA: Map data categories, purposes, retention, access, and cross-border flows; set review cadence.
- IP risk: Clarify ownership of prompts, outputs, fine-tunes; address third-party claims and content filters.
- Acceptable use: Guardrails for employees, shadow IT controls, and human review for high-impact tasks.
- Incident response: Joint playbooks, contacts, timelines, and evidence handling.
- Monitoring: Ongoing evals for accuracy, bias, and safety; drift alerts and rollback plans.
- Regulatory map: Track EU/US/Canada requirements by use case; keep an obligations matrix.
- Liability: Fit-for-purpose warranties, capped indemnities, IP and data breach coverage, and step-in rights.
- Exit: Data export, model artifacts, fine-tune portability, and verified deletion.
Inside Cohere's legal engine
At Cohere, legal and business strategy move together. Starostin credits a cross-functional team covering privacy, regulatory affairs, commercial contracting, IP, corporate governance, compliance, and employment law.
Many issues are new, especially in IP. He tells young lawyers to bring curiosity, ambition, and resilience. "As lawyers, if you can be the voice of calm and reason and make your stakeholders feel that no matter what, you've got this and we're going to figure it out together, that makes you the best kind of ally one can imagine."
Upskilling your legal team
If your team needs a fast, practical ramp on AI concepts, governance, and vendor selection, curated training helps. See a focused set of options by role here: AI courses by job.
Your membership also unlocks:
