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How to Evaluate AI Vendors

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As organizations increasingly adopt AI tools to streamline operations and enhance product offerings, in-house legal teams play a critical role in ensuring these implementations are both compliant and secure. Vendor agreements, which often serve as the foundation for these partnerships, require careful negotiation and scrutiny. From data usage rights to liability protections, in-house counsel must navigate a labyrinth of legal and operational considerations to safeguard their organizations. Here, we outline best practices for contracting with AI vendors and ensuring robust data security.

Key Data Considerations When Evaluating AI Vendors

Before entering into a contractual relationship with an AI vendor, legal teams must assess the risks and ensure the vendor’s capabilities align with organizational needs and compliance requirements. Critical factors to evaluate include:

  • Inputs: Confirm whether the vendor’s system requires access to sensitive data, such as personal information, trade secrets, or proprietary business data. Specify what types of data are permissible for input.

  • Outputs: Determine ownership of AI-generated outputs. Many vendors claim rights to reuse or train on output data unless explicitly restricted.

  • Secondary Uses: Scrutinize whether the vendor retains rights to use your data for purposes beyond providing the service, such as model training or product improvement.

Drafting Strong Vendor Agreements

Vendor agreements should clearly delineate the responsibilities and liabilities of both parties. Legal teams should prioritize the following clauses to minimize risk:

1. Data Rights and Restrictions:

  • Define permissible uses of input data and require vendor commitments to not use data for unauthorized purposes.

  • Include clear ownership terms for outputs, ensuring your organization retains control over AI-generated content.

  • Prohibit the vendor from using your organization’s data to train or improve their models unless explicitly authorized.

2. Warranties and Indemnities:

  • Include warranties that the vendor’s AI models and tools do not infringe on third-party intellectual property rights.

  • Secure indemnities for potential claims arising from unauthorized data usage, breaches, or other liabilities linked to the vendor’s services.

3. Termination and Data Disposal:

  • Clearly define conditions under which the agreement can be terminated.

  • Require secure deletion or return of your organization’s data upon termination, with certification of data destruction.

Balancing Risk and Innovation

AI adoption comes with risks, but overly restrictive policies can stifle innovation. Striking the right balance involves negotiating limited rights for vendors to use data for model improvement while implementing safeguards like anonymization and aggregation.

Risk mitigation should be tailored to the specific AI use case; for instance, customer-facing tools may need stricter controls than internal applications. Collaboration across teams—including product, engineering, and compliance—is essential to ensure AI tools are integrated effectively and aligned with contractual and security requirements.

Preparing for Future Regulatory Changes

To future-proof vendor agreements, require vendors to comply with all applicable laws and regulations, including any new ones introduced during the contract term.

Agreements should also include change management clauses that allow for renegotiation or updates to terms when regulatory changes arise. Clearly outline procedures for addressing new legal or compliance requirements that may affect the vendor’s services.

Staying informed about emerging AI regulations and industry standards is critical. Legal teams can proactively address potential impacts by engaging with industry groups and legal networks to anticipate changes that may affect vendor relationships.

Conclusion

For in-house counsel, navigating the complexities of AI vendor agreements and data security requires a proactive, detail-oriented approach. By focusing on robust data protections, clear contractual terms, and ongoing oversight, legal teams can enable their organizations to harness the benefits of AI responsibly. While the landscape remains uncertain, thoughtful planning and collaboration with internal stakeholders and vendors can position your organization for success in this transformative era.