As artificial intelligence (AI) continues to drive transformative innovation across industries, companies are turning away from traditional patent protections and embracing trade secret law to safeguard their most valuable assets—proprietary algorithms and datasets. With the fast pace of AI development and the high risks associated with patent invalidation, trade secrets offer a more adaptable and durable legal strategy.
Historically, patents were the preferred method for protecting intellectual property. But in recent years, a decline in patent litigation has coincided with a rise in trade secret disputes. This shift is largely due to the lengthy and often unpredictable patent process, coupled with vulnerabilities in the system such as the reduction of damages by courts and frequent invalidation by the Patent Trial and Appeal Board. Trade secret law, by contrast, allows companies to protect economically valuable, confidential information without disclosing it to the public.
Trade secrets are especially effective for protecting AI systems, which rely on undisclosed algorithms and proprietary datasets. These components are often integral to a company’s competitive edge but are difficult to patent under current U.S. laws, particularly after the 2022 Thaler v. Vidal ruling, which confirmed that AI systems cannot be listed as inventors. By maintaining secrecy, companies can shield AI-generated innovations from competitors while avoiding the pitfalls of patent litigation.
To capitalize on the advantages of trade secret protection, companies should implement comprehensive safeguards. These include legal agreements such as non-disclosure clauses and restrictive covenants, alongside technical measures like restricted system access, secure internal networks, and bans on external recording devices. In today’s AI-driven economy, that secrecy could represent a company’s most valuable asset.
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