The landscape of patent eligibility for machine learning (ML) technologies has become increasingly complex due to divergent interpretations by the U.S. Patent and Trademark Office (USPTO) and the U.S. Court of Appeals for the Federal Circuit. This discord presents significant challenges for innovators seeking to protect their ML inventions.
In April 2025, the Federal Circuit addressed the patent eligibility of ML applications in Recentive Analytics, Inc. v. Fox Corp. The court held that patents merely applying generic ML techniques to new data environments, without disclosing improvements to the ML models themselves, are ineligible under 35 U.S.C. § 101. The court emphasized that claims must articulate concrete technological advancements rather than merely applying established methods to different domains. This decision underscores the necessity for patent applications to demonstrate specific technological improvements in ML processes to meet eligibility criteria.
Conversely, the USPTO has exhibited a more accommodating stance toward ML-related patents. The agency’s guidelines suggest that ML inventions may be patentable if they are integrated into a practical application that results in a specific improvement in technology or a technical field. This perspective allows for a broader interpretation of what constitutes patent-eligible subject matter in the realm of ML.
The disparity between the Federal Circuit’s stringent requirements and the USPTO’s more flexible approach creates uncertainty for applicants. An invention deemed patentable by the USPTO may later be invalidated by the courts if it fails to meet the Federal Circuit’s criteria for technological improvement. This inconsistency complicates the patenting process for ML innovations and may deter investment in this rapidly evolving field.
To navigate this complex environment, applicants should focus on clearly delineating how their ML inventions contribute to technological advancements. This involves detailing specific improvements to ML models or demonstrating how the application of ML techniques leads to enhancements in a particular technical field. By aligning patent applications with the Federal Circuit’s emphasis on technological improvement, innovators can better position their inventions for both USPTO approval and judicial scrutiny.
As ML continues to permeate various industries, achieving a harmonized standard for patent eligibility is crucial. Such alignment would provide clearer guidance for innovators and foster a more predictable legal framework, ultimately encouraging continued investment and development in ML technologies.