US v Heppner’s Lessons for Canada: 
AI Use, Confidentiality and IP Exposure

AI Insights and Fast Reads

This AI Insights Quick Read series examines a growing risk for innovation-driven businesses: how routine generative AI use can weaken confidentiality, compromise legal review, and erode the value of intellectual property. Across four short pieces, we consider the issue through the lens of US v. Heppner, then turn to shadow AI, the dilution of innovation through AI-generated content and the implications for Canadian organizations.

Lessons for Canada

The first three pieces in this series focused on the core mechanics of AI-related IP risk, namely disclosure, unmanaged use and the dilution of innovation through superficial review. For Canadian organizations, preserving control over confidential know-how remains the central issue

Although Heppner is a US decision and turns on its facts, the practical lesson is relevant to Canada. If legally or commercially sensitive information is provided to a third-party AI system under terms that do not preserve confidentiality, the organization may be weakening the very protections it later hopes to invoke.

This is particularly relevant in Canada, where many businesses rely heavily on confidential know-how, technical methods, software workflows, data practices, customer information, manufacturing processes and early-stage invention records as a core component of enterprise value. Once secrecy is compromised, the practical value of those assets can erode quickly, often before any court dispute arises.

There is also a patent strategy dimension. Canada’s grace period may reduce the impact of certain inventor-derived disclosures for Canadian filings, but it is not a general cure. It does not restore trade secret status, does not address privilege risk and does not protect filing strategies in other jurisdictions. For Canadian companies with cross-border operations or international patent strategies, an ill-considered AI upload can therefore have outsized consequences.

Canadian organizations should be especially mindful of three practical points:

1. Privilege sensitivity: solicitor-client privilege is treated as a foundational protection in Canada. Unmanaged AI use involving legal advice or litigation strategy can create serious risk where confidentiality terms, retention or access controls are unclear.
2. Cross-border data handling: many AI services process or store information outside Canada. Governance therefore intersects with privacy, cybersecurity, procurement and records-management obligations, not just "innovation" policy.
3. Resource constraints: mid-market and research-driven organizations, like universities, may be most attracted to low-friction or "free" tools and least able to maintain disciplined review and approval processes conditions under which shadow AI tends to grow.

A practical takeaway is to treat confidentiality as infrastructure and part of your culture. If a company wants to preserve IP value while using AI, it should implement approved AI environments, clear internal restrictions on uploads, counsel-directed workflows for legally sensitive tasks, prompt/data hygiene rules and training that helps reviewers distinguish a polished summary from a protectable insight.

In practice, rights are often lost incrementally through convenience, inconsistent controls and unmanaged disclosure paths. Heppner is a useful reminder that AI governance is now part of IP risk management.

Across each part of this series, the same lesson emerges, AI risk in the IP context is rarely just about the output. It is about control over information, the quality of judgment applied to innovation and whether organizations are preserving or undermining the rights they expect to rely on later.

Explore the Full AI Insights Quick Read Series

For a deeper look at how generative AI impacts confidentiality, privilege, and intellectual property value, explore the full series:

• Part 1: US v. Heppner: The End of “Just a Prompt” and Emerging IP Risk
• Part 2: Shadow AI: The Unmanaged Use That Creates Real IP Disclosure Risk
• Part 3: AI Generated “Slop” and Overreliance on Summaries: How IP Value Gets Diluted

If you would like to learn more about the opportunities and risks associated with artificial intelligence, we invite you to contact the authors of this series or any member of our Artificial Intelligence group.