Shieldbase
Sep 4, 2024
Evaluating AI Vendor Contracts: Key Considerations for Businesses
As artificial intelligence becomes increasingly integrated into business operations, organizations must exercise caution when entering into vendor contracts involving AI technologies. With vendors frequently making ambitious promises about AI or AI-enhanced services, it is essential to assess these contracts with a critical eye. Below are the key factors to consider during the contract review process.
Definition and Scope of AI
To begin, it's important to establish a clear and comprehensive definition of "AI" within the context of the contract. A broad definition that encompasses various AI processes and applications, such as machine learning, algorithmic decision-making, and predictive analytics, is recommended. This approach helps ensure the contract remains relevant as AI technologies continue to evolve.
Due Diligence and Transparency
Thorough due diligence on both the vendor and the AI system itself is a crucial step before entering into any AI vendor contract. Key areas of investigation should include:
The vendor's reputation, past performance, and any potential legal issues.
The AI model's origins, architecture, training data sources, and potential biases.
The vendor's quality control measures and bias mitigation strategies.
Transparency regarding AI usage is also critical, especially as regulatory frameworks increasingly mandate disclosure when AI is in use. It may be prudent to include contractual provisions that require:
Disclosure of AI usage in consumer-facing services or products.
Prompt notification of any issues with the AI system, such as downtime or lawsuits that could impact service delivery.
Protocols for issue remediation and potential suspension of services.
Data Handling, Intellectual Property, and Confidentiality
Data is the cornerstone of AI systems, making it essential to address data handling and intellectual property rights within the contract. Ownership and usage rights should be clearly defined for:
Input data provided by the company, with copyright preferably retained by the company.
Outputs generated by the AI system, again with the company ideally owning the copyright.
Additional considerations include whether the AI vendor is using your company’s data to train its models, which could raise data privacy or HIPAA concerns. Confidentiality provisions should be in place to protect both input and output data.
Moreover, the contract should stipulate data-security measures, such as encryption protocols and data breach notification procedures. Compliance with applicable privacy laws and regulations must be explicitly required.
Intellectual property considerations extend beyond data. Negotiate appropriate indemnification for potential IP infringement claims, and consider licensing arrangements for the continued use of AI-generated content after contract termination if those rights are granted upfront.
Performance Standards and Accountability
Establishing clear performance metrics for AI, including accuracy, reliability, and bias mitigation, is vital. Consider incorporating service level agreements (SLAs) with specific performance targets, along with the right to terminate the contract if these targets are not met. The contract should also address the AI system's scalability to meet increased demand.
To ensure ongoing accountability, include provisions for regular audits or assessments of the AI system and continuous monitoring for bias throughout the AI's lifecycle.
Regulatory Compliance and Risk Allocation
The contract must clearly delineate responsibility for ensuring that the AI tool complies with applicable laws. This is particularly important given the rapidly evolving regulatory landscape surrounding AI, with new laws likely to emerge at both state and municipal levels. For example, Colorado was the first U.S. state to enact a comprehensive AI law. It is advisable to include provisions that allow for adaptation to new AI regulations as they arise.
Carefully define each party's responsibilities, including indemnification and limitations of liability. Address potential risks such as AI errors, biases, or unintended consequences. Expanded indemnification clauses may be necessary to cover AI-specific risks that standard contract language does not adequately address.
As the AI landscape continues to change, working closely with legal counsel is crucial to ensuring contracts remain current and aligned with best practices. By thoughtfully considering these elements, companies can better safeguard their interests and mitigate risks when engaging AI vendors.
