74 THE US-ISRAEL | Legal Review 2025/26 the expectations of acquirers operating within US and EU regulatory environments. This cross-border importation of risk expectations increasingly influences the content of Israeli acquisition agreements, including AI-related R&Ws and more nuanced indemnification mechanics. Another factor influencing Israeli M&A activity in recent months is the depreciation of the US dollar against the NIS, which has had a meaningful twofold impact on the market. As most Israeli M&A transactions and investment rounds are denominated in US dollars, while a substantial portion of companies’ operating expenses – particularly salaries and local services – are incurred in NIS, the weakening USD effectively reduces the purchasing power of invested capital when converted into local currency. This dynamic places pressure on companies’ operating budgets and runways, and in some cases prompts parties to revisit valuation assumptions, deal structures, or negotiation dynamics. Enterprise Value in 2025: From Revenue Multiples to Technological Infrastructure Technology acquisitions have historically emphasized revenue multiples, growth rates, and defensible intellectual property. In 2025, however, many AI-driven transactions appear to anchor value in what might be described as technological infrastructure: assets that may not be fully reflected in current revenue but are central to future scalability. Such infrastructure includes proprietary datasets, curated and continuously refreshed training pipelines, integration layers between AI models and enterprise systems, and engineering teams capable of sustained iteration post-closing. In AI-centric targets, the legal durability of these components directly affects enterprise value. A model’s performance depends, inter alia, on the legality and usability of its data pipeline. A platform’s defensibility depends on enforceable toolchain terms, open-source compliance discipline, and robust assignment and confidentiality frameworks. For transactional counsel, the key insight is that governance and value are no longer separable. Where the core asset is an AI system, its long-term utility is contingent on documented compliance with data rights, tool licenses, and information security controls. This linkage becomes even more pronounced when AI is embedded in physical systems. From Software AI to Physical AI: A Transactional Inflection Point According to Jensen Huang, founder and CEO of NVIDIA, “The ChatGPT moment for robotics is here. Breakthroughs in physical AI – models that understand the real world, reason, and plan actions – are unlocking entirely new applications”. There is a growing consensus that AI is now entering the era of physical AI: creating systems that understand the real world, interact with it, and perform physical tasks, not merely generate text or images. Much of the public discourse surrounding AI has focused on software-only applications. Yet an increasing proportion of deep-tech innovation, within Israel and globally, is deployed into physical environments: robotics, medical devices, industrial automation, autonomous mobility, and other cyber-physical systems. From an M&A perspective, physical AI materially alters the risk profile of target companies. While failures in software-based AI typically give rise to contractual disputes, data protection exposure, or regulatory scrutiny relating to data use, failures in physical AI systems such as robotics, autonomous devices, or AI-enabled hardware may lead to bodily injury, property damage, regulatory investigations, and multi-jurisdictional product liability claims. Because physical AI systems interact directly with the physical environment, their potential failure modes are broader and the magnitude of potential harm is significantly greater, fundamentally altering the risk calculus in M&A transactions. As a result, diligence and risk allocation must assess not only model performance and data governance, but also real-world validation, system safety, and operational reliability. Buyers are increasingly requesting expanded and tailored R&Ws and covenants addressing product safety, regulatory compliance, and incident management. These requests are typically paired with more detailed disclosure obligations, including engineering documentation, safety validation and testing evidence, change-management or modelrelease procedures, and records of prior incidents or near-misses. The diligence exercise is therefore both retrospective and forward-looking: assessing whether systems have been tested under diverse operating conditions, whether model updates follow documented release and quality-assurance processes, and whether monitoring, incident response, and remediation practices are embedded within the organization. Where material gaps or uncertainties are identified, parties increasingly allocate lifecycle and product-risk exposure through targeted indemnities, enhanced warranty frameworks, and structured escrows or holdbacks.
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