The Expanding Prevalence Of AI Clauses In Contracts

Artificial Intelligence (AI) is rapidly transforming the business world, moving from a niche technology to an integral part of operations across nearly every industry. Whether you are acquiring a technology company or simply using AI services such as customer chatbots or data analysis programs, businesses are being exposed to a new class of legal risks. To address these unique challenges, businesses and investors are increasingly including AI-specific representations and warranties in contracts and agreements. These clauses are becoming a crucial method for effectively allocating and mitigating AI-related uncertainty.

Risks, Benefits, and Key Considerations

While the benefits of AI in terms of efficiency and pattern recognition are immense, the technology also presents novel and significant legal risks. The importance of AI technology in business means that acquirers are now seeking tailored assurances even when a target's AI use is not material to the core business, recognizing that any unmanaged risk can lead to future liability.

Key AI Risks and Considerations

• Intellectual Property (IP) Infringement and Ownership: AI models, particularly GenAI tools, are trained on vast datasets that may contain web-scraped data, images, text, or other content protected by copyright. Developers are increasingly facing allegations that their tools were trained by "ingesting protected content without a license." This creates a risk of infringement claims against both the developer and the user of such AI tools. There also remains uncertainty over the extent of IP protection for both AI inputs and content created by AI.
• Data Quality and Bias: AI outputs are only as good as the inputs. If the data used to train an AI model is inaccurate, biased, or otherwise flawed, the resulting model and its outputs may be equally flawed. Users of AI services should ask how the data used to train the model was sourced. This risk must be addressed through careful due diligence.
• Data Privacy: Large datasets used to train machine learning models may inadvertently incorporate personal, sensitive, or inaccurate information. Public generative AI tools cannot guarantee deletion or non-retention, as any information submitted is used to further refine the model. Beyond the risks associated with personal information, companies need to ensure that their employees do not disclose sensitive company IP or customer information to a publicly accessible system.

Types of AI Representations and Warranties

AI-specific representations and warranties that go beyond standard IP and technology warranties are a method for buyers and investors to obtain contractual assurances that risks unique to AI have been addressed. These specialized clauses can tailor risk allocation by assigning responsibility for AI-specific issues to the seller, backstop the buyer's due diligence by providing contractual assurances, and offer a clear path for recourse (like indemnity) if a post-transaction lawsuit arises. The inclusion of AI clauses can help protect investments and mitigate exposure.

Common Topics Addressed by AI Clauses

• Data Use and Training Data: Warranties concerning the target company's rights to use data for AI training and assurances as to the source, accuracy, and ownership of the training data set are being more frequently utilized. A clause may require a specific representation that the AI model was trained only with permissioned data (i.e., data that was obtained through legally binding consent or licenses for use). For companies using third-party GenAI, a representation may require the disclosure of the specific tools being utilized and the terms of the applicable license.
• Intellectual Property: Clauses certifying ownership of AI-specific assets, such as algorithms, models, and parameters, can be included in contracts. For example, a clause may state that the user or licensee will own the IP for any works generated by the AI model, especially when a model is used for product design or content creation. These clauses may also address the risk of infringement associated with a model's training and output, such as through indemnification provisions in service contracts.
• Governance and Compliance: Contracts may now include assurances that there are internal AI governance frameworks, including documented policies for testing and monitoring, "human in the loop" requirements, and that the entity complies with any applicable AI laws and regulations. A representation might be that no AI models or platforms were utilized in the generation of a product, or that all employees have signed a data use agreement that prohibits entering any company information into GenAI models.

Conclusion

The market for generative and agentic AI is expanding rapidly, and AI clauses will only become more common. Failing to understand the AI utilization of a business and to address AI risk contractually is an enterprise-level weakness. Downstream non-compliant service providers or contractors may taint any upstream use of data and create liability. Companies must be prepared to answer questions about their use of AI tools and processes. Even if not contemplating a sale or acquisition in the near future, questions about AI use are now appearing as part of the underwriting and renewal process for certain liability and cyber insurance policies. Close reading of any contractual provisions relating to the use of AI or AI-generated data is necessary, as is ensuring compliance with existing restrictions.

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