AI Contracting: Emerging Risks and Best Practices
Artificial intelligence is reshaping contractual frameworks, introducing new risk, responsibility, and commercial considerations. Organizations must adapt to these changes to protect themselves and ensure compliance.
Ownership of AI‑Generated Outputs
Canadian intellectual property law currently requires a human creator for ownership, leaving AI‑generated outputs in a legal gray area. Until courts and legislators clarify this, contract parties should define ownership structures that allocate rights to the appropriate entity and outline permissible uses of AI outputs.
Data Confidentiality and Secondary Use
Disclosing information to public AI models can incorporate that data into training sets, creating a risk of reproduction and unintended exposure. Even with enterprise AI solutions, contracts should address potential secondary uses—such as training data for model improvement—to mitigate data leakage.
Privacy Protections
When personal information is involved, contracts must include robust privacy protections and mandate a privacy impact assessment. This helps identify data‑leakage pathways, such as disclosure to third‑party model providers, and ensures compliance with privacy regulations.
Indemnities and Liability Shifts
Recent AI model provider contracts are introducing indemnity clauses that shift liability away from end users. Parties should scrutinize these clauses to confirm that the selected AI model and its intended use fall within the indemnified scope, especially regarding IP infringement and output errors.
Future‑Proofing Contracts for AI Regulation
Anticipated AI regulations necessitate contracts that can adapt to new legal requirements. Including off‑ramps and amendment mechanisms allows organizations to respond to regulatory changes without renegotiating the entire agreement.
Responsibility for AI‑Generated Errors
In professional services where AI tools are employed, contracts should allocate responsibility for AI‑generated errors and hallucinations. Consider provisions that address potential damages from reputational harm or reduced value of deliverables.
Sovereign AI and Model Governance
The rise of sovereign AI—locally controlled models without foreign infrastructure ties—offers a strategic avenue for reducing geopolitical risk. Organizations may prioritize sovereign solutions to maintain data sovereignty and regulatory alignment.
AI Agents and Oversight
Deploying autonomous AI agents raises questions about agent permissions, context retention, and the need for genuine human oversight. Contracts should define permissible agent actions and establish safeguards to prevent loss of context or unintended behavior.
Alignment with Established AI Risk Frameworks
Adopting recognized standards such as NIST’s AI Risk Management Framework or ISO/IEC 23894:2023 demonstrates a proactive approach to risk mitigation. Aligning contracts with these frameworks helps organizations articulate defensible risk‑management strategies.
Conclusion
As AI continues to integrate into commercial activities, contracts must evolve to address ownership, confidentiality, privacy, liability, regulatory adaptability, and governance. By embedding clear terms, indemnities, and alignment with industry standards, organizations can navigate the emerging AI landscape while minimizing exposure to legal and operational risks.
