By Ryan Abbott. Professor Abbott, MD, JD, MTOM, PhD, is Professor of Law and Health Sciences at the University of Surrey School of Law, Adjunct Associate Professor of Medicine at the David Geffen School of Medicine at UCLA, partner at Brown, Neri, Smith & Khan, LLP, and a mediator and arbitrator with JAMS, Inc.

Recently, the Federal Circuit handed down its decision in Recentive v. Fox which the Court stated presented a question of first impression: “whether claims that do no more than apply existing methods of machine learning to a new data environment are patent eligible.” Recentive Analytics, Inc. v. Fox Corp., 134 F.4th 1205 (Fed. Cir. 2025). As the framing of the question suggests, the Court answered in the negative, confirming that patents that simply take an abstract idea and “do it with AI” are not statutory subject matter.

Since this decision, questions have come up about what this might mean for the patenting of inventions relating to artificial intelligence (AI) in the United States, and by extension, America’s leadership in AI development. Even before this case, the argument has been made that getting patents on AI innovations is difficult or impossible under the current law, and therefore patent eligibility reform is needed. These are important questions. As I have argued for years in my work on the Artificial Inventor Project, and as I testified on in Congress, AI technology is playing a rapidly growing role in the innovation process. We want to make sure the patent system is promoting the development and use of AI so that it can be used to generate socially valuable innovation (and that there are no legal concerns when that happens, including related to inventorship).

My view is that current patent eligibility law as it pertains to abstract ideas best supports the AI development and innovation that we need in the United States. The current approach permits the patenting of all aspects of AI technology – from the development and training of machine learning models to the applications of those models. Recentive gave us a glimpse into how patent eligibility law applies at one end of the AI patenting spectrum, and it reached the right conclusion.

Before delving into Recentive, it is helpful to understand the application of patent eligibility law in a traditional software patenting context. Eligibility analysis relies on the two-step Alice/Mayo test, which first determines whether claims are directed to judicial exceptions to eligible matter, namely abstract ideas, laws of nature, or natural phenomena. Alice Corporation v. CLS Bank International, 573 U.S. 208 (2014); Mayo Collab. Servs. v. Prometheus Lab’ys, Inc., 566 U.S. 66 (2012). If claims are directed to a judicial exception then to be patent eligible they must recite additional elements that amount to “significantly more” than the judicial exception. Mayo, 566 U.S. at 72-73. The Supreme Court has described the second part of the test as the search for an “inventive concept”. See MPEP § 2106. This is the Supreme Court’s way of ensuring that a true, technological invention lies at the heart of the patent and that it isn’t just an abstract idea dressed up to look like a real invention.

For more than a decade, the Alice/Mayo two-part test has been the exclusive test for software patent eligibility analysis. It balances patent incentives with the need to allow the public to utilize “the basic tools of scientific and technical work.” Alice Corp., 573 U.S. at 216. Patents on such tools could do more harm than good and “might tend to impede innovation more than it would tend to promote it.” Id. Claims are not ineligible simply because they involve judicial exceptions, the applications of such concepts remain protectable. Indeed, the Federal Circuit has subsequently clarified that claims directed to software and improvements in computer-related technologies are not inherently abstract. See, e.g., Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335 (Fed. Cir. 2016); see also Visual Memory LLC v. NVIDIA Corp., 867 F.3d 1253, 1258 (Fed. Cir. 2017). Judicial exceptions have existed for more than 150 years, and a significant amount of case law has now applied Alice/Mayo in the context of software patents.

The Federal Circuit has tended to require patent applications to describe specific improvements over the prior art that improve a process, whether software- or hardware-based, rather than merely performing an existing process on a computer. This has allowed a wide range of computer-implemented claims to be found patent-eligible. See, e.g., McRO Inc. v. Bandai Namco Games America Inc., 837 F. 3d 1299 (Fed. Cir. 2016); Amdocs (Israel) Ltd. v. Openet Telecom Inc., 841 F. 3d 1288 (Fed. Cir. 2016); Ancora Technologies Inc. v. HTC America Inc., 908 F. 3d 1343 (Fed. Cir. 2018). This standard thus encourages research and development into improvements in computer processes, while preventing applicants from broadly tying up the use of computers to perform existing processes and relying on functional claiming (e.g., filtering content on a computer, unless an improvement over the prior art for filtering content; parsing, editing, sorting, and comparing data, absent a specific inventive method for carrying out these functions). See BASCOM Glob. Internet Servs., Inc. v. AT&T Mobility LLC, 827 F.3d 1341, 1348 (Fed. Cir. 2016); see Berkheimer v. HP Inc., 881 F.3d 1360, 1366 (Fed. Cir. 2018).

With the foundation of applying patent eligibility law to traditional software patents, we can more fully understand the Federal Circuit’s assessment of patent eligibility in an AI context in Recentive. This case concerned the eligibility of using machine learning, a subset of AI, to generate network maps and schedules for television broadcasts and live events. Recentive was appealing the district court’s ruling that its patents were directed to ineligible subject matter under 35 U.S.C. §101. The Federal Circuit affirmed the lower court on the basis that the patents lacked an inventive concept and were directed to the abstract idea of using a generic machine learning technique in a particular environment.

Preparing network maps is a long-standing practice, if a sophisticated and niche one that has traditionally been performed by human beings. Recentive characterized its patents as applying existing, generic AI approaches to this specific context. In other words, “do it with AI.”

This type of “do it with AI” claim is ineligible under the two-step Alice inquiry.  On the first step, the Court found that the claims were directed to the abstract idea of producing network maps and event schedules using known standard mathematical techniques. Recentive’s patent did not claim or describe how the machine learning technology resulted in a technological improvement. Instead, the patent was just about using AI to perform a task previously done by humans more quickly or efficiently without actually explaining how to accomplish that, which does not create eligibility. This is the same application of the Alice/Mayo test to traditional software patents.

On the second step, which looks at whether additional elements add an “inventive concept” that transforms an otherwise ineligible claim, the Court also found the patents failed. The patents only provided broad, functionally described common computing techniques and devices—again merely claiming an abstract idea.

While the Court framed Recentive as a question of first impression, the Federal Circuit has long held that software claims do not become eligible by limiting their application to a particular field or environment – eligibility does not result from taking an abstract idea and throwing in “do it on a computer” or “do it over the internet.” See, e.g., Intell. Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1366 (Fed. Cir. 2015). Similarly, that applying an existing technology to a new database does not create eligibility.  See, e.g., SAP Am., Inc. v. InvestPic, LLC, 898 F.3d 1161, 1168 (Fed. Cir. 2018). Like the software patent cases that came before it, Recentive just applied AI to an existing framework.

While simply describing an abstract idea and adding “do it with AI” is not patentable (nor should it be), patent protection is available for all aspects of AI innovation. Practitioners have outlined best practices for drafting these patent applications, emphasizing the importance of providing sufficient detail and explaining the technical advantage of the claimed solution. https://www.fr.com/insights/thought-leadership/articles/ai-patent-eligibility-observations-and-lessons-for-the-us-and-china/ (“The key for applicants is to clearly show that their claim improves a technological process rather than merely uses technology to perform an existing process.”) https://www.troutman.com/insights/locke-lord-quickstudy-patenting-ai-inventions.html. (“Draft a strong patent application… Focus on technical aspects and algorithms… Provide experimental evidence and results…”). Of course, applicants must also ensure what is being claimed is commensurate with what was actually invented and not improperly tying up the basic tools of further scientific development. The USPTO’s most recent guidance on patent subject matter eligibility in 2024 provided some examples as well.  See, e.g., https://www.uspto.gov/sites/default/files/documents/2024-AI-SMEUpdateExamples47-49.pdf.

Recent district court decisions applying Recentive have also upheld claim eligibility for AI-related claims. Aon Re, Inc. v. Zesty.AI, Inc., No. CV 25-201, 2025 WL 1938214 (D. Del. July 15, 2025) (“The claim thus implements machine-learning technology in a specific way to address a practical technical problem: how to accurately and quickly assess the physical characteristics and condition of a property from an aerial image using machine learning models.”); Nielsen Co. (US), LLC v. Hyphametrics, Inc., No. CV 23-136-GBW, 2025 WL 1672002 (D. Del. June 13, 2025) (Claimed method provides “an improvement to the technical field of image processing, and, in particular, to improving speed and reliability of detecting overlays in images, with reduced or eliminated human oversight… These claims contain structure because they, inter alia, recite the specific [neural] networks used to perform the detection”).

Though all aspects of AI can be patented under Alice – and our patent eligibility law aims to ensure that AI patents do not over-claim in a way that would harm further AI innovation and usage – AI has nonetheless become yet another argument in support of patent eligibility reform. Various changes have been proposed over the past decade to expand the scope of section 101. Most recently, Senator Thom Tillis re-introduced the Patent Eligibility Restoration Act (PERA) in the Senate. https://www.congress.gov/bill/119th-congress/senate-bill/1546/text. This Act would eliminate all judicial exceptions to patent eligibility, replacing them with explicit and narrow statutory exclusions: 1) a mathematical formula not integrated into a claimed invention; 2) a mental process performed solely in the human mind; 3) an unmodified human gene as it exists in the human body; 4) an unmodified natural material as it exists in nature; and 5) a process that is primarily economic, financial, business, social, cultural, or artistic in nature. Most relevant to the issue of AI patenting, and what would be patent-eligible if PERA were to become law, the bill includes an eligibility escape hatch. It states that “the claimed invention shall not be excluded from eligibility for a patent if the invention cannot practically be performed without the use of a machine or manufacture.” This would mean that any abstract ideas could be patented if implemented on a computer leveraging computational capabilities. Effectively all AI inventions “cannot practically be performed without the use of a [computer].” This means that under PERA, “do it with AI” patents like the one found to be ineligible in Recentive would be eligible.

As a result, PERA would be a significant shift for patent eligibility of computer-related patents, and one that would harm rather than help the development and use of AI. Problematically, by untethering patent eligibility for abstract ideas from the requirement that patents be about technological improvements, PERA would allow patents that harm the development and widespread usage of actual technology. This in turn is likely to result in more patent thickets which will make AI development increasingly difficult and expensive, it will give incumbents more leverage over startups, and it risks holdups from foreign adversaries abusing the patent system. This is precisely the type of approach that allowed a flood of “do it on a computer” and “do it on the internet” patents to harm software development and usage for years. It is not a standard that is likely to help the United States remain the world’s leader in AI development.      Nor is it a standard that will support innovators using AI as part of their development process.

And that is where our focus should lie: making sure our patent system is helping to incentivize AI technology development and usage in order to move the field forward. Patent eligibility has a pivotal gatekeeping role in the system, as the Federal Circuit correctly showed in Recentive. The line that has been drawn and applied in a software context for years is also the right one for AI.

The author represents that he is not being paid to take a position in this post. In addition to being an academic, the author is a practicing attorney and represents clients with interests on both sides of the post’s subject matter.

by Dennis Crouch

The federal government shutdown that began at 12:01 AM on October 1, 2025, is creating a patchwork of disruptions across the nation’s intellectual property infrastructure, with each major system affected differently based on their funding structures. The Copyright Office is apparently completely shuttered, its staff unable to access email or respond to inquiries.

As I discussed yesterday, the USPTO remains operational by drawing on fee-based reserve funds built up over recent years.  But, the new news is an announced 1% workforce reduction (~1500 people) today along with closure of its Denver Office as part of “mission-prioritization.”  Interestingly, the agency cited to a Biden-era report to Congress that “physical office space is less necessary” primarily because of the successful telework policies. The current administration has taken extensive steps to eliminate those policies. [Updated to fix my math – 150 people fired, not 1,500.]

by Dennis Crouch

In Rideshare Displays, Inc. v. Lyft, Inc., No. 2023-2033 (Fed. Cir. Sept. 29, 2025) (nonprecedential), the Federal Circuit affirmed the PTAB determination that claims directed to vehicle identification systems for ridesharing services were unpatentable for obviousness, but reversed the Board’s grant of Rideshare’s motion to amend substitute claims. Judge Hughes, writing for the panel, held that the substitute claims were directed to patent-ineligible subject matter under 35 U.S.C. § 101 because they merely used technology as a tool to improve user experience rather than improving computer functionality itself.

The patents at issue all share a common specification directed to systems and methods for vehicle identification that allow ridesharing app users to verify they are getting in the correct cars and drivers to confirm they are picking up the correct riders. U.S. Patent Nos. 9,892,637; 10,169,987; 10,395,525; 10,559,199; and 10,748,417.  The systems work by having a driver’s device receive a notification signal that triggers an indicator visible from outside the car, such as a code or icon on a display. Lyft filed five petitions for inter partes review in November 2021, and the Board found all challenged claims unpatentable as obvious or anticipated over the prior art.  Rideshare moved to amend claims in two of the proceedings, and the Board allowed several substitute claims, prompting Lyft’s cross-appeal challenging the amendments on patent eligibility, written description, and obviousness grounds.

In its decision, the court compared the claimed system to “hand-printed cards with names to help identify ride pickups at crowded locations, such as an airport,” finding that invoking computers and mobile devices to streamline human interactions does not transform an abstract idea into patent-eligible subject matter.

USPTO's Limited Authority Over Substantive Patent Law

The USPTO lacks interpretive authority to construe substantive patent statutes including 35 U.S.C. §§ 101, 102, 103, and 112. The agency's internal guidance documents directing how patent examiners and even PTAB judges must apply these provisions receive no deference from reviewing courts. The Federal Circuit independently interprets these statutory provisions de novo, applying its own precedent rather than deferring to administrative interpretations. Here, for example, the court explicitly declined to follow the USPTO's 2019 eligibility guidance framework which I have previously noted tends toward being more pro-eligibility than court precedent.

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by Dennis Crouch

The Federal Circuit reversed a Texas jury’s $166 million infringement verdict in Finesse Wireless LLC v. AT&T Mobility LLC, 24-1039 (Fed. Cir. Sept. 24, 2025), holding that the patentee’s contradictory and unclear expert testimony could not support the Jury’s finding of patent infringement.  The case is centered on  Finesse’s U.S. Patent Nos. 7,346,134 and 9,548,775, which relate to methods of reducing “intermodulation interference” in wireless communications.

Chief Judge Moore, writing for a unanimous panel, emphasized that when a patentee’s infringement case rests on “self-contradictory testimony” from its expert, courts “may conclude the evidence is insufficient” to satisfy the burden of proof.  But in this case, the panel didn’t just note the possibility of insufficient evidence – it actually applied the rule against the patentee. After analyzing Dr. Wells’s contradictions, the opinion held: “This sort of confusing change of course is not sufficient to support the jury verdict.”

This decision underscores the Federal Circuit’s escalating demands on expert testimony in patent cases. It shows up at two levels: (1) parties must marshal “their” experts to walk the jury through virtually every technical or patent‐law issue; and (2) the expert’s testimony must be internally consistent, tightly tied to the record, and conveyed with particularized precision.  I’ve written on this new hurdle that is typically focused on patentee-presentations.  See Federal Circuit Tightens Expert Testimony Standards in Trudell, Patently-O (Feb. 2025); Throwing Out the Jury: How the Federal Circuit’s ‘Particularized Testimony’ Rule Further Threatens the Doctrine of Equivalents, Patently-O, (May 2025); Wilco v. Weeks Marine: When Expert Disagreements Don’t Create Genuine Disputes of Material Fact, Patently-O (Aug. 2025); and The Remedies Remedy is Almost Complete: EcoFactor v. Google, Patently-O (May 2025). (more…)

by Dennis Crouch

The Federal Circuit recently handed down its decision in Bayer Pharma Aktiengesellschaft v. Mylan Pharmaceuticals Inc., No. 2023-2434 (Fed. Cir. Sept. 23, 2025), focusing on the the claim limitation “clinically proven effective.”  Bayer’s U.S. Patent No. 10,828,310, which claims methods for reducing cardiovascular events in certain patients by administering specific doses of rivaroxaban (2.5 mg twice daily) and aspirin (75-100 mg daily) “in amounts that are clinically proven effective.” Generic manufacturers Mylan, Teva, and Invagen successfully challenged the patent in IPR proceedings — finding the claim term non-limiting.  The Federal Circuit agreed that the term did not provide patentable weight – but through a different analytical path.

Clinically Proven Effective: Contrasting Analytical Approaches

The PTAB concluded “clinically proven effective” was non-limiting, reasoning that because the claims already recited specific dosage amounts (2.5 mg rivaroxaban twice daily and 75-100 mg aspirin daily), the additional characterization of these amounts as “clinically proven effective” was merely redundant. Drawing on Bristol-Myers Squibb Co. v. Ben Venue Labs., Inc., 246 F.3d 1368 (Fed. Cir. 2001), the PTAB found the phrase constituted an “expression of intended result [that] essentially duplicates the dosage amounts recited in the claims.”

On appeal though, the Federal Circuit took a markedly different approach, declining to decide whether “clinically proven effective” was limiting at all. Instead, the court applied the functional relationship test from King Pharms, concluding that even if the phrase were limiting, it constituted a “functionally unrelated limitation” that could not rescue an otherwise anticipated method from unpatentability. The court reasoned that clinical proof of efficacy “in no way transforms the process of taking the drug[s]” at the specified amounts and frequencies, emphasizing that the “the actual method . . . is the same” regardless of subsequent clinical validation.

The Functional Relationship Test from King Pharmaceuticals

In King Pharmaceuticals v. Eon Labs, 616 F.3d 1267 (Fed. Cir. 2010), the Federal Circuit established an important test for determining when additional claim limitations can make an otherwise anticipated method patentable. The case involved patents claiming methods of taking the muscle relaxant metaxalone with food to increase the drug's bioavailability - a practice that was already disclosed in prior art for reducing stomach upset. The patentee argued that adding a step of "informing" patients about the increased bioavailability made the claims novel. The Federal Circuit rejected this argument, holding that the relevant inquiry is whether the additional limitation has a "new and unobvious functional relationship" with the known method. Since informing patients about the drug's benefits "in no way transforms the process of taking the drug with food" and "the actual method . . . is the same" regardless of whether patients are informed, the informing step lacked the required functional relationship. This test prevents patentees from indefinitely extending patent protection over known methods by simply adding instructional, informational, or other functionally unrelated steps that don't change how the method actually works.

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