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In the landscape of AI innovation<\/a><\/b>, successful outcomes frequently hinge on forming strategic partnerships<\/b>. This could involve a cloud provider<\/b> delivering essential infrastructure<\/b>, a specialized developer<\/b> providing tailored models, or a data vendor<\/b> supplying critical inputs. While these collaborations can accelerate product development, they come with inherent risks. If a vendor’s system encounters a malfunction, breaches regulations, or mishandles data, your company bears the consequences. Therefore, it is crucial to establish robust frameworks to mitigate these risks.<\/p>\n For in-house counsel<\/b>, the vendor agreement serves as a vital instrument to transform uncertainty into definitive, enforceable expectations. This process transcends mere legal protection; it establishes the foundational principles for how the AI<\/b> will be developed, maintained, and governed throughout the entire duration of the partnership. By prioritizing clarity and accountability, organizations can better navigate the complexities of their vendor relationships.<\/p>\n Clearly Defining Responsibilities in AI Contracts<\/strong><\/p>\n Every AI contract<\/b> should commence with a clear and unambiguous delineation of responsibilities. If the system yields harmful outcomes, fails to meet accuracy benchmarks, or breaches applicable laws, the agreement must specify who is held accountable. This delineation encompasses performance standards, quality control measures, and obligations for promptly resolving any issues that arise. Ensuring accountability is essential for maintaining trust and upholding quality in AI systems<\/b>.<\/p>\n Furthermore, compliance with regulations<\/b> cannot be taken for granted. Vendors must commit to adhering to relevant laws and inform your organization immediately if any legal changes necessitate adjustments to the system or its deployment. By ensuring clear lines of responsibility, companies can effectively manage potential risks associated with their AI partnerships<\/b>.<\/p>\n Ensuring Operational Transparency for AI Systems<\/strong><\/p>\n To effectively manage risk, it is imperative to gain comprehensive visibility into the AI system<\/b>. This necessitates including contractual rights to access thorough documentation that elucidates how the system operates, the origins of its data, and the methodologies it employs to reach conclusions. Such transparency allows organizations to remain informed and prepared.<\/p>\n This documentation may take various forms, including technical summaries, disclosures regarding training data, and change logs that detail updates. Without this essential information, organizations may find themselves unprepared when regulators request specific details or when customers challenge the decisions made by the product. Therefore, ensuring operational transparency is crucial for maintaining compliance and building trust.<\/p>\n Clarifying Ownership and Usage Rights in AI Agreements<\/strong><\/p>\n In the realm of AI projects<\/b>, the intricacies of intellectual property<\/b> rights are often complex. The contract should explicitly outline ownership of the model, ownership of the outputs generated, and whether the vendor has the authority to utilize your data to enhance its technology for other clients. Establishing clear terms prevents potential misunderstandings regarding licensing scope, exclusivity, and restrictions concerning the reuse of your proprietary information or derived datasets.<\/p>\n By including these specifications, organizations can avoid disputes that may arise long after the product has entered the market. Clear ownership and usage definitions create a foundation for collaboration and ensure that each party understands its rights and responsibilities.<\/p>\n Establishing Data Governance Standards for AI<\/strong><\/p>\n Data serves as the vital lifeblood of AI<\/b> and is often the source of various legal risks. Therefore, contracts must delineate explicit rules regarding how the vendor will manage your data, encompassing aspects such as storage security and deletion protocols. Organizations should proactively determine whether production data can be leveraged for further training or testing, and under what safeguards such actions are permissible.<\/p>\n Implementing robust governance clauses is essential for maintaining compliance with privacy regulations<\/a><\/b> and aligning with your organization\u2019s internal data policies. By establishing rigorous data governance standards, organizations can better navigate the complexities of data management in the context of AI<\/b>.<\/p>\n Adapting to Changes Over Time in AI Projects<\/strong><\/p>\n AI systems are dynamic and continuously evolving. Vendors may update models, integrate new datasets, or modify processing methodologies. As such, the contract should stipulate the requirement for notifying your organization of any significant changes, as well as your right to approve such modifications before they are deployed. This proactive approach ensures that the evolving nature of AI<\/b> does not compromise compliance or safety.<\/p>\n Termination rights are also vital in these agreements. Your organization should retain the ability to exit the relationship if any changes threaten compliance, safety, or business alignment. Securing these protections is generally more straightforward at the onset of the partnership than during a crisis.<\/p>\n Utilizing Contracts as Strategic Instruments for AI Partnerships<\/strong><\/p>\n An AI vendor contract<\/b> functions as more than just a means of allocating risk. When crafted effectively, it guarantees that the vendor\u2019s operations align with your organization\u2019s regulatory obligations, ethical commitments, and overarching business priorities. Such contracts provide the necessary insights and control to deploy AI responsibly<\/b>, even when the core technology originates outside your organization.<\/p>\n For in-house counsel<\/b>, moving from generic boilerplate language to customized AI clauses<\/b> entails developing agreements that not only safeguard trust but also encourage collaboration. A well-constructed contract does not merely shield the company from potential harm; it also facilitates partnerships that yield AI solutions<\/b> that are reliable, compliant, and in harmony with the strategic goals of the business.<\/p>\n Olga V. Mack<\/em><\/strong> is the CEO of TermScout, an AI-powered contract certification platform that accelerates revenue and eliminates friction by certifying contracts as fair, balanced, and market-ready. A seasoned CEO and legal tech executive, she previously led a company to a successful acquisition by LexisNexis. Olga is also a <\/em><\/strong>Fellow at CodeX, The Stanford Center for Legal Informatics<\/em><\/strong>, and the Generative AI Editor at law.MIT. She is a visionary leader transforming the legal landscape\u2014redefining how legal systems are constructed, experienced, and trusted. Olga <\/em><\/strong>teaches at Berkeley Law<\/em><\/strong>, lectures extensively, and advises organizations of various sizes, as well as boards and institutions. An award-winning general counsel turned entrepreneur, she also spearheads early-stage ventures including <\/em><\/strong>Virtual Gabby (Better Parenting Plan)<\/em><\/strong>, <\/em><\/strong>Product Law Hub<\/em><\/strong>, <\/em><\/strong>ESI Flow<\/em><\/strong>, and <\/em><\/strong>Notes to My (Legal) Self<\/em><\/strong>, each innovating the practice and business of law through technology, data, and human-centered design. Olga has authored <\/em><\/strong>The Rise of Product Lawyers<\/em><\/strong>, <\/em><\/strong><em>Legal Operations in the Age of AI and Data<\/em><\/a><\/strong>, <\/em><\/strong>Blockchain Value<\/em><\/strong>, and <\/em><\/strong>Get on Board<\/em><\/strong>, with Visual IQ for Lawyers (ABA) forthcoming. A 6x TEDx speaker, she has been recognized as a Silicon Valley Woman of Influence and an ABA Woman in Legal Tech. Her work reimagines the relationship between people and law\u2014making it more accessible, inclusive, data-driven, and aligned with contemporary realities. She is also the host of the Notes to My (Legal) Self podcast (available on <\/em><\/strong>Spotify<\/em><\/strong>, <\/em><\/strong>Apple Podcasts<\/em><\/strong>, and <\/em><\/strong>YouTube<\/em><\/strong>), with her insights frequently featured in Forbes, Bloomberg Law, Newsweek, VentureBeat, ACC Docket, and Above the Law. Olga earned her B.A. and J.D. from UC Berkeley. Connect with her on <\/em><\/strong>LinkedIn<\/em><\/strong> and X @olgavmack.<\/em><\/strong><\/em><\/strong><\/p>\n