For large corporations, the primary concern when adopting AI models from overseas is not peak performance but regulatory risk. The possibility that a chosen model could be banned by future government action is a greater deterrent than technical limitations, as large companies cannot pivot their tech stack quickly.

Despite security concerns, US companies might adopt Chinese open-source models like GLM because they can be hosted on US hardware with no data leakage. The immense cost savings and ability to maintain full control over the stack make them a practical alternative to expensive, risky frontier models.

The sudden unavailability of a top-tier proprietary AI model reveals a critical business risk. Enterprises now see open-source models, run on local hardware, not just as a cost-saver but as a necessary strategy for predictable access and business continuity.

A growing number of companies, especially in regulated industries like finance and healthcare, are opting for open-source AI models they can run on-premise. This trend is driven by concerns over data leakage, IP security, and national data sovereignty, creating a distinct market need for more domestic, controllable AI solutions separate from frontier models.

While currently promoting open-source AI, the Chinese Communist Party will inevitably lock down powerful models once they are capable of sophisticated cyber operations. The risk of domestic groups, like Tibetan separatists, using these tools to challenge state control like the Great Firewall is a threat the CCP will not tolerate.

DeepSeek's V4 model, while not frontier-level, is drastically cheaper than US counterparts. This makes it highly attractive for most business use cases, creating a national security risk if US companies become dependent on Chinese-controlled, open-source AI infrastructure that could be altered or restricted, leaving them strategically vulnerable.

As Silicon Valley startups increasingly adopt cheaper Chinese AI platforms, a political backlash is likely. The US government may block their use, citing national security risks and data privacy concerns, mirroring past restrictions on Chinese EVs and telecom hardware.

Despite the superior performance of models like Kimi K3, widespread business adoption in the West is unlikely. Geopolitical tensions and the risk of building infrastructure on Chinese AI are significant deterrents, with governments on both sides considering export controls and bans.

While concerns about propaganda in Chinese AI models exist, they can be mitigated through post-training. The greater strategic risk is a scenario where leading open-source models are architected to run best on Chinese hardware like Huawei chips, making the US dependent on China's hardware ecosystem.