AI patents face higher invalidation rates than software, USPTO data shows

The systematic disadvantage for AI patents in court threatens the legal stability of core streaming innovations, from recommendation engines to automated encoding. As invalidation rates climb, companies may shift toward trade secrecy, reducing industry-wide technical transparency and complicating cross-platform licensing. This legal vulnerability suggests that current B2B IP portfolios in video tech may be overvalued if they rely heavily on generic AI implementations rather than technical improvements to the underlying hardware or models. Watch for a rise in Section 101-based motions to dismiss targeting AI-centric streaming features in 2026.

The shifting legal landscape for AI patents has been further complicated by recent federal court rulings and regulatory recalibrations. In April 2025, the U.S. Court of Appeals for the Federal Circuit issued a decision in Recentive Analytics, Inc. v. Fox Corp., which legal observers at Davis Polk and Finnegan described as a critical case of first impression. The court held that claims merely applying generic machine learning to new data environments—such as broadcasting schedules—are patent-ineligible under 35 U.S.C. § 101. This ruling reinforced the 'abstract idea' doctrine, suggesting that without specific improvements to the computer or AI model itself, automated processes remain highly vulnerable in litigation.

Simultaneously, the U.S. Patent and Trademark Office (USPTO) has moved to provide clearer pathways for applicants to avoid these pitfalls. Under Director John A. Squires, who took office in late 2025, the agency issued guidance in April 2026 formalizing Subject Matter Eligibility Declarations (SMEDs). Per Sigma Law Group and Stradling, these documents allow applicants to submit a structured factual record from technical experts during prosecution. The goal is to establish that an AI invention produces a concrete technical improvement beyond what a human mind could replicate, potentially building a more resilient record for future appeals or litigation.

Despite these new administrative tools, volume in AI-related litigation continues to surge. According to reports from Cornerstone Research and DOAR in early 2026, AI-related copyright and patent filings reached a major inflection point in 2025, with patent filings jumping from under 20 cases annually to nearly 100 within a single year. This growth is driving a strategic pivot toward trade secrets, particularly as firms seek to protect model weights and proprietary datasets that standard patent law currently struggles to cover under existing inventorship and eligibility frameworks.