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human decision-making and have not been authoritatively applied to autonomous AI systems. We believe our 
provision of intelligence service is considered a “service” in the context of legal frameworks addressing product 
liability, but courts and regulators may reach different conclusions across jurisdictions. In addition, it is unclear 
whether, and under what circumstances, actions taken by an AI agent could be deemed to create binding legal 
obligations  on  behalf  of  the  user  or  deploying  enterprise,  or  whether  our  contractual  protections,  including 
limitation of liability and indemnification provisions, will be enforceable or adequate in the context of claims 
arising from autonomous agent conduct. We may face claims from customers, their end users, or third parties 
alleging  that  we  are  liable  for  harm  caused  by  our  agents’  autonomous  actions,  even  where  the  customer 
configured,  deployed,  or  supervised  the  agent.  The  absence  of  settled  legal  standards  creates  significant 
uncertainty regarding our potential liability exposure and the adequacy of our risk mitigation measures.

Our  expansion  into  new  geographic  markets  further  compounds  these  risks,  as  we  must  navigate  differing 
cultural norms regarding AI use, comply with diverse and evolving regulatory regimes that may impose varying 
safety, compliance, or liability requirements, address language-specific vulnerabilities and content moderation 
challenges,  and  potentially  face  regulatory  enforcement  actions,  litigation,  or  other  liabilities  in  jurisdictions 
where  we  have  more  limited  operational  experience,  including  heightened  risks  of  intellectual  property  theft, 
unauthorized model access, or misuse associated with operating data center infrastructure in certain non-U.S. 
locations.

If our models are involved in causing significant harm, we could be subject to legal claims, including personal 
injury  or  negligence  claims,  regulatory  enforcement  actions,  criminal  investigations,  or  other  governmental 
efforts,  which  could  result  in  costly  litigation,  significant  financial  judgments  or  settlements,  disruptive 
remediation  obligations,  or  a  challenging  regulatory  landscape.  We  have  taken  steps  to  limit  our  liability  for 
such matters—for example, through warranty disclaimers and limitations of liability in our terms of service—
but those contractual protections may not be upheld, or may not apply to certain claims, or may otherwise be 
insufficient to limit our liability exposure under applicable law. Moreover, in some cases we have contractually 
assumed  additional liability.  For  example,  to  facilitate  independent  testing  and  evaluation  of  our  frontier 
models, we have agreed to indemnify certain external evaluators and testing vendors for specified losses arising 
from testing activities, including security incidents, data loss, data breaches, and other harms associated with 
such  activities. Although  our  agreements  with  external  evaluators  and  testing  vendors  generally  limit  the 
amount of our indemnification obligations, certain of these agreements require us to defend and indemnify the 
evaluator, without a cap on our liability, against certain third-party claims. These include claims arising from 
allegations that our models or their outputs, as used in the evaluator’s authorized testing, infringe third-party 
intellectual  property  or  other  proprietary  rights,  as  well  as  certain  other  claims  arising  from  the  testing  or 
related engagement. Because our models may behave in ways that no user or developer intended, claims arising 
from  such  actions  could  result  in  substantial  liability.  Our  insurance  policies  also  may  not  provide  sufficient 
coverage to adequately mitigate the potential liabilities we face, especially where any one incident, or a group of 
incidents,  causes  disproportionate  harm.  In  addition,  with  the  scale  of  harm  that  could  result  from  a 
catastrophic AI-related incident, no single insurer, and potentially the insurance industry in the aggregate, may 
have sufficient capacity or expertise to underwrite insurance commensurate with such exposure.

Further,  the  insurance  market  for  AI-specific  risks  is  nascent  and  evolving,  and  we  may  be  unable  to  obtain 
coverage  for  certain  AI-related  liabilities  on  commercially  reasonable  terms,  or  at  all,  leaving  us  exposed  to 
potentially significant uninsured losses. Harmful incidents involving our models, regardless of fault, could also 
severely and disproportionately damage our reputation and brand as a safety-focused AI company, leading to 
loss of customer trust and customer attrition, reduced demand for our models, platform, and applications, and 
difficulty attracting and retaining talent. In addition, because we primarily serve enterprise customers, which 
often  have  heightened  expectations  around  safety,  reliability,  and  compliance,  any  harmful  incident  or 
perceived  lapse  in  our  safety  practices  could  have  a  disproportionate  adverse  impact  on  our  brand,  customer 
relationships,  and  revenue.  Moreover,  to  the  extent  enterprises  are  attracted  to  our  models,  platform,  and 
applications  due  to  our  safety-focused  positioning,  any  erosion  of  that  perception  could  impair  our  ability  to 
attract and retain enterprise customers.

There can be no assurances that we will be able to predict, detect, and proactively prevent every harmful use or 
harmful  output  of  our  AI  models,  in  particular  as  we  continue  to  rapidly  develop  our  models,  platform,  and 
applications,  and  expand  our  operations  geographically,  and  any  failure  to  do  so  could  adversely  affect  our 
reputation  and  brand  or  result  in  costly  legal  liability.  There  may  have  been  past  instances  of  harmful  use  or 

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