76 THE US-ISRAEL | Legal Review 2025/26 tooling and generative AI usage R&Ws, and broader AI development and training representations. In some acquisition agreements, sellers have provided stand-alone AI R&Ws addressing compliance with internal AI policies and third-party AI tool terms. Such provisions often include confirmations that sensitive PII, trade secrets, or other confidential information have not been included in prompts or inputs to external AI tools, subject to carefully drafted carveouts for tools that do not train on user inputs. They may also address ownership of outputs and require disclosure of dependencies on AI technologies in the disclosure schedules. Other agreements have gone further, requiring a complete and accurate inventory of AI tools, products, and training datasets used in development, operation, or improvement of AI systems. Sellers have represented that required licenses and permissions have been obtained for each training dataset and that controls have been implemented to mitigate risks of regurgitation, copyright infringement, trade secret misappropriation, or harmful outputs. In some instances, sellers have also represented ownership of models created, trained, or fine-tuned using the company’s proprietary data. These R&Ws serve a practical function: they translate evolving legal uncertainty into contractual risk allocation. Even where the legal status of AI outputs and training inputs continues to develop across jurisdictions, acquisition agreements allocate risk between the parties. Where AI is embedded in products, AI R&Ws increasingly appear alongside traditional productliability R&Ws. Sellers may represent the absence of product recalls, governmental notices of violation, or material safety claims. In physical AI transactions, such provisions function as disclosure-forcing mechanisms and create pathways for targeted indemnities or separate liability caps where safety exposure is identified. Software AI vs. Physical AI Key Negotiation Differences While AI-related diligence and R&W packages have become increasingly common across Israeli technology transactions, the negotiating center of gravity varies depending on the role AI plays in the target’s business. In some cases, AI is merely adjacent to the core product or activity – for example, through the use of generative AI tools – whereas in others it is the primary value driver, whether deployed as software or embedded in physical products. From an M&A perspective, the distinction is therefore less about sector and more about the nature of the risks a buyer assumes at closing and the contractual mechanisms available to allocate those risks. In pure software AI transactions, the central risk categories typically include: » ownership of core IP and employee invention assignment; » open-source software contamination; » lawful and durable rights to data and privacy compliance; » dependency on third-party tooling or model providers; and “...in modern AI M&A, enterprise value is determined not solely by what the company owns at signing, but by whether the buyer can lawfully, safely, and sustainably operate and evolve the acquired system over time.”
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