Negotiating AI Vendor Contracts

Negotiating artificial intelligence (AI) vendor contracts is an important step in ensuring businesses secure terms that protect their interests while optimising the value of AI solutions. Unlike standard software agreements, AI contracts must address specific challenges, including regulatory compliance, liability, data protection, and long-term adaptability.

European and Swiss businesses must navigate evolving legal frameworks, such as the EU AI Act or Swiss data protection regulations, while also ensuring AI vendors uphold transparency, accountability, and risk mitigation. This article explores key negotiation strategies to help businesses secure AI vendor agreements that are legally sound and commercially advantageous.

Understanding Business Needs and Regulatory Obligations

Before negotiating with vendors, businesses should clearly define their objectives and understand the legal framework governing AI use in their industry. Key considerations include:

• Intended Use of AI: Establishing the AI tool’s specific function, expected outputs, and its role within business operations.
• Regulatory Compliance: Ensuring the AI system meets applicable legal and industry standards, including the EU AI Act, GDPR, Swiss data protection laws, and sector-specific regulations that may impose additional requirements on AI deployment.
• Long-Term Viability: Assessing whether the AI solution aligns with long-term business strategies and technological developments.

Entering contract negotiations without a well-defined strategy increases the risk of accepting terms that do not meet business requirements.

Negotiating Vendor Responsibilities and Performance Standards

AI systems do not deliver fixed outputs, meaning performance standards must be explicitly defined to avoid disputes. Contracts with AI technology vendors could outline:

• Performance Metrics: Accuracy levels, response times, uptime guarantees, and corrective measures in case of underperformance.
• Model Evolution and Updates: Transparency on how AI models evolve and ensuring businesses can test updates before deployment.
• Explainability and Accountability: Requiring vendors to provide documentation detailing how AI decisions are made, particularly in high-stakes applications.
• Ongoing Support and Maintenance: Clearly defining vendor obligations for troubleshooting, technical support, and periodic performance reviews.

Businesses should push for measurable commitments rather than vague assurances that leave room for disputes.

Securing Data Rights and Privacy Protections

AI systems rely heavily on data, making it imperative that businesses maintain control over their information and meet regulatory obligations. Key negotiation areas include:

• Ownership of Data and Outputs: Ensuring businesses retain full rights to the data they input and the insights generated by the AI tool.
• Restrictions on Vendor Use of Data: Preventing vendors from using proprietary data to improve their models for other clients unless explicitly agreed.
• Right to Data Erasure: Establishing clear rights for businesses to demand the deletion of their data when the contract ends.

Failing to address these aspects may result in loss of control over valuable data assets or inadvertent regulatory breaches.

Mitigating Liability and Managing Risk Allocation

Liability is a critical issue when procuring AI solutions. AI systems do not always behave predictably, and if they produce incorrect, biased, or harmful results, businesses need to be protected from financial and legal consequences. Vendors often try to minimise their exposure, but businesses should negotiate liability terms that fairly allocate risk.

• Managing Vendor Liability and Indemnification: Businesses should carefully assess liability disclaimers to ensure vendors take appropriate responsibility for AI-related errors, malfunctions, and compliance failures. Depending on the level of risk, businesses may consider negotiating indemnification provisions covering claims related to AI failures, training data, outputs, confidentiality breaches, and regulatory compliance issues.
• Negotiate Reasonable Liability Caps: Some vendors propose low liability caps that do not reflect the potential risks posed by AI errors. Businesses should negotiate realistic caps that take into account the financial and reputational impact of AI failures.
• Insurance Requirements: Businesses can require vendors to maintain insurance policies covering AI-related risks, including data breaches, regulatory fines, and third-party claims.

Clearly defined liability terms prevent businesses from bearing excessive financial or legal consequences due to AI malfunctions.

Maintaining Flexibility and Future-Proofing Contracts

AI technology advances rapidly, and businesses must ensure vendor contracts allow for adaptability. Essential negotiation points include:

• Exit and Termination Rights: Ensuring businesses can terminate contracts if AI performance declines, regulatory non-compliance arises, or better alternatives become available.
• Avoiding Vendor Lock-In: Guaranteeing businesses can transition to alternative providers without excessive exit fees or technical restrictions.
• Regulatory Change Provisions: Requiring vendors to update AI models to comply with evolving laws or allowing businesses to terminate agreements if compliance cannot be ensured.

Contracts that lack flexibility may leave businesses tied to outdated or non-compliant AI solutions.

How we can help

Negotiating AI vendor contracts requires businesses to be strategic, informed, and assertive. By securing well-defined vendor obligations, retaining data control, and negotiating fair liability terms, businesses can ensure they extract maximum value from AI solutions while minimising risks. If you need a well-structured AI vendor contract, schedule a free 20-minute discussion with our technology lawyers. We will help you negotiate and secure favourable terms that align with your business objectives.

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