AI Patent Invalidation Rates Raise Questions About U.S. Innovation Policy
If courts are systematically applying stricter eligibility standards to AI-related patents than to comparable non-AI patents, the gap between White House AI ambition and federal judicial practice...
AI-related patents are facing higher invalidation rates and lower infringement-finding rates in U.S. federal courts compared to patents in other technology categories, according to an August 2026 analysis published by the Washington Examiner citing patent litigation data. The disparity, attributed to judicial application of the Supreme Court's 2014 Alice Corp. v. CLS Bank International ruling (573 U.S. 208), creates what the analysis describes as a two-stage disadvantage for AI patent holders: increased vulnerability at the validity stage and reduced success at the infringement stage.
The Alice decision established a two-step test for determining whether software and abstract-idea patents meet the eligibility requirements of 35 U.S.C. § 101. Since that ruling, the U.S. Court of Appeals for the Federal Circuit — the court with exclusive jurisdiction over patent appeals — has applied the framework in ways that critics contend are particularly restrictive for machine-learning and AI-related inventions. The precise invalidation rate differential between AI and non-AI patents has not been published in a single comprehensive federal dataset; the U.S. Patent and Trademark Office (USPTO) annual performance reports and the Federal Circuit's own statistical disclosures would be the primary public records capable of quantifying this gap.
The Trump administration has stated publicly that AI dominance is a national priority. Executive Order 14179, signed January 23, 2025, directed federal agencies to remove barriers to American AI development and directed the Office of Science and Technology Policy to coordinate a national AI action plan. That order did not address patent eligibility standards or direct the USPTO to issue new § 101 guidance specific to AI inventions, according to the text of the order published in the Federal Register (90 Fed. Reg. 9971).
The USPTO has previously issued subject-matter eligibility guidance — most recently updated in October 2019 under the prior administration — that attempted to clarify how examiners should apply the Alice framework. Whether the current USPTO director has initiated a rulemaking or guidance revision specific to AI patent eligibility is not confirmed in any published Federal Register notice as of the date of this report. A formal rulemaking would be documented in the Unified Regulatory Agenda and subject to public comment under the Administrative Procedure Act.
Congress holds the authority to amend 35 U.S.C. § 101 directly. Bipartisan legislative efforts to reform patent eligibility — including the Patent Eligibility Restoration Act introduced in the 118th Congress by Sens. Chris Coons (D-DE) and Thom Tillis (R-NC) — did not advance to a floor vote, according to the congressional record. No companion legislation has been confirmed as introduced in the 119th Congress as of this writing.
What remains unknown is the precise, agency-verified percentage difference in AI versus non-AI patent invalidation rates and the number of AI patents affected annually. The USPTO's Patent Trial and Appeal Board (PTAB) publishes inter partes review statistics quarterly; those filings, combined with Federal Circuit disposition data, would be the public records needed to produce a verified figure. It is also unknown whether the White House has directed the USPTO to prioritize § 101 guidance revision as part of the AI action plan implementation.