Machine Learning and Patent Eligibility: Recent Court Guidance and Claim Strategy

On Apr. 18, 2025, in Recentive Analytics Inc. v. Fox Corp. et al., the Federal Circuit struck down patents that claim machine learning for failing to recite patent eligible subject matter. This is the Federal Circuit's first time encountering AI in a 35 U.S.C. § 101 inquiry, ruling on "whether claims that do no more than apply established methods of machine learning to a new data environment are patent eligible." The Federal Circuit held "they are not."

Recentive Analytics follows the Electric Power Group line of cases, which holds that collecting information, analyzing it, and displaying it is an abstract idea. These three steps are performed in many AI systems, including machine learning, and thus, Electric Power Group and its progeny (including Recentive Analytics) pose a threat to AI systems.

Patent counsel should carefully consider the lessons from the Recentive decision as well as the entire Electric Power Group line of cases. What and how can the applicant do more and demonstrate the patent eligibility of AI, including machine learning?

Listen as our authoritative panel of patent attorneys addresses the Federal Circuit's Recentive decision, the Electric Power Group line of cases, and the lessons that can be learned. The panel will offer best practices for patent drafting strategies.

I. The patent eligibility of AI inventions

II. Electric Power Group line of cases

III. Recentive Analytics Inc. v. Fox Corp. (Fed. Cir. Apr. 18, 2025), including Federal Circuit reasoning and guidance

IV. Standards for eligibility

V. USPTO guidance

VI. Patent drafting strategies

The panel will review these and other relevant issues:

• What lessons does the Recentive decision teach as to the patentability of machine learning claims?
• What is the appropriate way to claim machine learning inventions?
• What steps should patent counsel take to meet patent eligibility requirements?