Meta has reportedly restricted some employees from using AI coding tools developed by rival companies over concerns that its internal systems could unintentionally extract proprietary knowledge from competing models.
According to a report by The Information, engineers working within Meta’s Applied AI team are no longer allowed to use Anthropic’s Claude Code or OpenAI’s Codex without prior approval. The reported restriction stems from concerns that Meta’s internal AI workflows may interact with these tools in ways that could inadvertently learn or replicate capabilities from competing AI models.
Such scenarios raise legal and ethical questions surrounding AI model distillation—the practice of reproducing the behavior or capabilities of another company’s AI system without authorization. As AI competition intensifies, companies are becoming increasingly cautious about protecting their intellectual property.
The report suggests this is among the first publicly known instances of a major AI company limiting employee access to competitors’ AI coding assistants specifically to avoid the risk of absorbing proprietary capabilities. However, Meta has not officially confirmed the report or clarified whether the restriction applies across the company or only to teams involved in AI model development.
The development also highlights broader concerns surrounding enterprise AI adoption. Although companies like OpenAI and Anthropic offer enterprise versions of their AI products with enhanced privacy protections, organizations remain cautious about exposing sensitive internal information that could potentially influence AI model training or compromise proprietary data.
Meta is not alone in taking such precautions. Several technology giants, including Apple, Samsung, and Amazon, have previously imposed restrictions on employees’ use of AI tools such as ChatGPT and GitHub Copilot over concerns that confidential code, trade secrets, or other sensitive information could be inadvertently shared with external AI systems.
As businesses continue integrating AI into their workflows, the challenge remains balancing productivity gains with the need to safeguard intellectual property and confidential corporate data.
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