Software patents are failing at an alarming rate. In 2020, courts rejected 85% of software patent appeals—23 out of 27 cases lost everything. The Alice/Mayo test has become the biggest threat to software innovation protection, but the companies that understand this test are securing patents while their competitors get nothing.
Courts evaluate Alice software patents using this test from the US Supreme Court. The test decides if a software invention can get a patent or if it’s too abstract. This guide explains how the test affects software patents and helps you secure patents for your software ideas.
Key Takeaways
- Understanding the Alice/Mayo test helps determine if software can get patent protection, making sure patents support innovation instead of blocking abstract ideas.
- Showing specific tech improvements beyond basic computer use is key to passing the Alice test and getting software patent protection.
- Smart drafting techniques for patent claims should focus on real results and specific advances to boost approval chances and fight rejections.
Understanding the Alice Software Test
The Alice/Mayo test uses a two-step process to check if an invention deserves patent protection. This method combines several legal decisions and became the main way to assess patent eligibility after the Supreme Court decided Alice Corp v. CLS Bank International. The court said that some software innovations count as abstract ideas and can’t get patent protection. Patent attorneys must analyze inventions thoroughly to see if they meet the Alice/Mayo test requirements.
The Supreme Court’s Alice ruling has dramatically limited patents based on abstract concepts that just use standard computer technology. The ruling also reduced unclear software patents. District courts play a big role in interpreting the Alice framework, often conducting their own eligibility analysis separate from USPTO examiner reasoning. This change has given companies stronger defenses against “patent trolls” who used vague software patents to sue startups and smaller companies.
AI inventions must follow the Alice/Mayo examination rules to qualify for patent grants. These rules ensure that issued patents help technological progress and knowledge while preventing overly broad claims from hurting innovation in industries that depend on these advances. The Manual of Patent Examining Procedure (MPEP) and patent office guidance tell examiners how to analyze eligibility, outlining the step-by-step process for determining if claims can get patents under the Alice framework.
Successfully handling software patent approval requires understanding this essential review process, including the importance of determining eligibility.
Understanding the Three Categories of Abstract Ideas in AI Patent Claims
When working with AI patent applications, understanding how the USPTO categorizes abstract ideas in AI claims is crucial. The 2024 USPTO guidance provides clearer rules on this distinction, which matters because AI technologies often use mathematical concepts, algorithms, or computational techniques.
The USPTO identifies three main categories of abstract ideas that may appear in AI patent claims.
Mathematical Concepts
These include mathematical relationships, formulas, equations, and calculations. Since many AI technologies use complex algorithms and statistical methods, this category often applies to AI inventions. However, experienced attorneys have successfully argued that claims don’t include mathematical concepts when they just base themselves on mathematical principles without explicitly stating mathematical formulas or calculations in the claim language.
Methods of Organizing Human Activity
While less common in AI inventions, this category may show up in applications involving AI-driven financial systems, business methods, or workflow optimization. This commonly appears in claims related to AI systems that automate traditional business processes.
Mental Processes
These cover concepts that could theoretically be done in the human mind, such as observations, evaluations, judgments, and opinions. Importantly, the USPTO guidance says that claims don’t include mental processes when they contain limitations that can’t practically be performed in the human mind. This exception often applies to AI inventions that process massive datasets or perform complex calculations beyond human thinking ability—a distinction attorneys regularly use in practice.
The key insight is that when evaluating whether an AI invention includes an abstract idea, the USPTO carefully distinguishes between claims that explicitly “recite” an abstract idea (requiring further eligibility analysis) and those that merely involve or base themselves on an abstract idea without putting it into the actual claim language.
Step Two: Determining Inventive Concepts in Software Claims
In the second phase of the Alice/Mayo test, determining if an inventive concept that significantly improves the abstract idea exists within a claim becomes the focus. This essential component can transform what might be seen as a patent-ineligible abstract idea into an application that qualifies for patent eligibility. The main purpose is to establish whether additional elements exist in the claimed invention that raise its status beyond just executing an abstract notion.
During the evaluation process, attorneys must figure out whether these claim elements are common and ordinary or considered conventional practices. An inventive concept can show up through advances that improve how computers operate or through developments applied to other technological fields. Especially for AI innovations, showing specific technical progress rather than broad applications becomes crucial for meeting the inventive concept requirement. Claims with specific technical solutions are more likely to qualify as patent eligible applications under the Alice/Mayo framework.
The documentation that comes with a patent—the patent specification—must clearly outline both a distinct technical challenge and its solution. This serves as evidence supporting the inventive aspect of the proposal and critically supports the inventive concept. Improvements related to computer functionality or other tech areas remain focal points during examination by both USPTO examiners and under broader review within America’s patent framework. Ultimately, this step prevents granting patents just for using abstract ideas, but instead recognizes inventions that contribute genuine advances in technology as patent eligible inventions, with the claimed method playing a key role in demonstrating eligibility.
Insufficient Elements: Generic Computer Implementation
Simply adding a basic computer setup to a patent claim doesn’t make an abstract idea eligible for a patent. Using generic computers doesn’t contain enough detail to satisfy the inventive concept requirement under the Alice framework. Common actions such as gathering data after finding a solution aren’t considered inventive. Routine data gathering steps and well-understood, routine, conventional activities aren’t enough to make claims patent eligible.
The inability to show an inventive concept with non-specific computer implementations and common procedures hurts one’s chance of meeting patent-eligibility requirements. For instance, if a claim only involves using a computer database for information storage without any particular technological improvements, it would likely fail under the Alice test by being categorized as an ineligible concept for patent protection.
Insignificant Post-Solution Activity
Patent claims that feature activities such as routine data gathering and other common actions fail to contribute to the inventive quality of a software patent. These standard procedures, including basic computation or manipulation, don’t meet the inventiveness criteria that the Alice test establishes. Examiners may consider such activities a judicial exception that doesn’t contribute to patent eligibility.
To avoid denial due to lack of significance, patent claims should highlight novel and creative components rather than ordinary or routine tasks. A claimed invention’s success under examination requires that it demonstrates how it leads to a distinct technological advancement.
Demonstrating Practical Application Integration for AI Inventions
Even when an AI invention includes an abstract idea, it can still qualify for patent protection if it integrates that abstract idea into a practical application. This critical assessment evaluates whether the claim as a whole applies, relies on, or uses the abstract idea in a way that meaningfully limits it.
Through analysis of numerous AI patent applications, one of the most effective strategies to demonstrate practical application integration involves showing that the AI invention improves how a computer or another technology functions. The USPTO calls this “a technological solution to a technological problem.”
For AI inventions specifically, attorneys focus on highlighting improvements such as:
- Better computer vision capabilities that solve previously unsolvable technical problems
- More efficient data processing techniques that reduce computational overhead
- Increased speed or accuracy in machine learning operations beyond conventional approaches
- Novel neural network architectures that address specific technical limitations
- Reduced computational resource requirements for equivalent performance
- Improved ability to handle noisy, incomplete, or corrupted data sets
The key distinction emphasized in practice contrasts claims that reflect genuine improvements to technology (which qualify as eligible) versus those that merely apply an abstract idea using generic computer components or simply link the abstract idea to a technological environment (which don’t qualify). This distinction often determines success or failure in overcoming Alice rejections.
Practical Application Integration for AI Inventions
The USPTO works to ensure clear and consistent assessments of AI-related patent claims, promoting innovation by confirming inventions satisfy the criteria for patent eligibility. The Patent Office evaluates whether claims constitute patent eligible applications and eligible subject matter by applying the standards that 35 U.S.C. § 101 and the Alice framework establish. Even when a claim revolves around an abstract idea, it may qualify for patent protection if integrated into a practical application that shows its concrete utility.
To help figure out how abstract ideas might evolve into eligible patents, the USPTO has provided guidance featuring examples such as anomaly detection and personalized medical treatment. These scenarios serve to show compliance with the standards that the 2019 Revised Patent Subject Matter Eligibility Guidance sets forth.
AI inventions can gain patent protection when they put an abstract idea within a functional application. An AI invention’s ability to improve how computers or other forms of technology operate supports this integration effectively. Adopting this practical viewpoint secures not only theoretical inventive concepts, but also those applied within tangible contexts, including software-based innovations.
Recent USPTO AI Guidance and Federal Circuit Decisions (2024-2025)
The patent eligibility landscape for AI and software has evolved significantly with recent developments. In July 2024, the USPTO released comprehensive AI-specific eligibility guidance, effective July 17, 2024, following a White House executive order that directed agencies to adapt to AI innovations. This guidance provides clarity on how examiners should apply the Alice/Mayo test to AI-related claims while maintaining the existing legal framework.
Landmark Federal Circuit Decision: Recentive Analytics v. Fox (2025)
A pivotal case emerged in April 2025 with Recentive Analytics, Inc. v. Fox Corp., marking the Federal Circuit’s first major ruling on AI and machine learning in the Alice context. The court held all four patents on using machine learning models to optimize TV broadcast schedules patent-ineligible as merely implementing an abstract idea with generic technology.
Judge Dyk, writing for the court, framed the critical issue: “whether claims that do no more than apply established methods of machine learning to a new data environment are patent eligible. We hold that they are not.” This decision reinforces that AI algorithms don’t receive special treatment under §101—if an AI/ML claim lacks specific technological improvement, it remains vulnerable to abstract idea exceptions.
The Recentive decision shows the challenges that attorneys regularly encounter when securing AI technology patents under current judicial conditions. Through innovative techniques, inventors can tackle these hurdles more effectively, often achieving significantly improved success rates for overcoming Alice rejections.
Survey of the 3 Key AI Patent Eligibility Examples from USPTO
The July 2024 USPTO guidance included three detailed Patent Eligibility Guidance (PEG) examples showing how the Alice/Mayo test applies to AI inventions across different domains. The USPTO designated these as “Examples 47-49” in their sequential numbering system, but only these 3 examples specifically focus on AI patent eligibility. These examples provide valuable insights for attorneys drafting AI-related patent claims and represent the most comprehensive guidance available for AI patent eligibility.
AI Patent Example 1: Anomaly Detection in Network Security
This example demonstrates AI-based network security through an artificial neural network (ANN) that detects anomalies and malicious activities. The USPTO analyzed three distinct claims:
Claim 1 (Eligible): An apparatus claim describing an application-specific integrated circuit that implements the ANN. Because it describes a concrete machine without abstract processes, it qualifies as eligible subject matter.
Claim 2 (Ineligible): A method that simply “leverages an artificial neural network to identify anomalies from a data set” without specific field of use or further action. This claim targets an abstract idea (data analysis) and lacks integration into a practical application.
Claim 3 (Eligible): Adds crucial additional steps by placing anomaly detection within network monitoring context and including responsive actions—determining malicious activity and taking remedial blocking measures. These concrete post-detection steps demonstrate practical network-security improvement, integrating the abstract idea into a practical application.
The key takeaway: merely using AI isn’t enough; claims must demonstrate technological application or improvement to satisfy Alice requirements.
AI Patent Example 2: Speech Separation Using Deep Neural Networks
This example involves AI-based audio signal processing to separate mixed audio signals into individual speakers’ voices using deep neural networks (DNNs).
Claim 1 (Ineligible): Broadly describes receiving mixed audio signals, converting them (e.g., into spectrograms), and applying DNNs for voice separation. This essentially describes mathematical data analysis without practical limitations, making it ineligible as it “recites a judicial exception (an abstract idea).”
Claim 2 (Eligible): Uses the same DNN-based analysis but specifies application context—improving speech-separation systems’ ability to isolate voices by generating enhanced audio outputs for transcription. This additional context demonstrates concrete improvement in speech-separation technology.
Claim 3 (Eligible): Extends the process further by improving speech-to-text transcription accuracy after voice separation, perhaps by filtering commands versus background conversation. This claim ties AI processing to concrete transcription technology improvements.
The lesson: AI-based signal processing methods should link to specific technical outcomes (clearer audio, better transcription) rather than claiming underlying mathematical operations.
AI Patent Example 3: AI in Medical Diagnosis and Treatment
This scenario addresses using AI for diagnosing and treating pulmonary fibrosis, demonstrating the interplay between abstract ideas and natural law exceptions in biotech applications.
Claim 1 (Ineligible): Features an AI algorithm that identifies fibrosis conditions from patient data, viewed as abstract data analysis involving natural phenomena (correlations between biomarkers and disease).
Eligible Claims: Link AI diagnosis to specific treatment steps, such as administering tailored therapy based on AI determinations. By connecting discovery to concrete treatment protocols, these claims transform abstract ideas/natural laws into practical healthcare applications that achieve real-world therapeutic outcomes.
This mirrors the Mayo precedent: pure diagnostic insights aren’t patentable, but methods that apply insights in treatment can be. In practice with AI in medicine, including active treatment or intervention steps is crucial for passing Alice/Mayo scrutiny.
Takeaway from the 3 AI Patent Examples: Across these examples, the common thread is that specificity and technical application matter. AI or software-related claims must do more than describe an abstract algorithm or data processing; they should emphasize how the invention improves technology or achieves a tangible result. The USPTO’s 3 AI patent examples show that adding elements like particular devices, fields of use, or follow-up actions (e.g., remedial steps, outputting a concrete product, treating a patient) can make the difference between ineligible and eligible subject matter. In practice, patent applicants in AI/ML learn to draft claims that highlight inventive technical contributions (such as improved accuracy, efficiency, or new functionality) to overcome Alice-based rejections.
Innovative Techniques for Overcoming Alice Rejections
Thompson Patent Law (TPL) has developed proprietary strategies that significantly enhance success rates in countering Alice rejections. These innovative techniques can improve the likelihood of overcoming such rejections by 25-50%, representing a substantial advantage for inventors who face these challenges.
These proven methods often save one to two years of time and considerably reduce prosecution expenses—often saving clients five figures in prosecution costs. This proves particularly valuable given that patents obtained through prolonged prosecution typically emerge weaker than those that examiners allow on first or second office actions, which typically happens for software applications at TPL.
For inventors who confront Alice rejections, strategic appeal considerations following correction of other rejection categories may offer fresh perspectives. Should initial claims face rejection, filing continuation applications provides means to adjust responses to evolving legal standards. Patent attorneys bring specialized expertise in navigating Alice rejections, analyzing claim elements, and formulating effective arguments for patent eligibility.
The latest modifications related to patent subject matter eligibility include scenarios that specifically help patent professionals when assessing AI innovations during examination phases. Using these methods results in stronger patents that are more likely to withstand scrutiny and meet criteria for patent eligibility.
Federal Circuit Decisions Impacting Software Patents
After the Alice verdict, the patent landscape for software inventions has become increasingly challenging. In 2020, only four out of twenty-seven software-related patent appeals passed through Section 101 scrutiny. The Federal Circuit has consistently applied strict standards, recently ruling on machine learning patent status and upholding that patents related to event scheduling optimization using standard machine learning techniques fell under judicial exceptions and therefore didn’t qualify.
The Court has held that if a patent merely applies common machine learning algorithms to perform tasks that humans can do manually, it doesn’t qualify for patent protection. Federal circuit judges have emphasized that using typical machine learning models fails to satisfy Alice test criteria unless inventors demonstrate technological improvements. District court decisions have further reinforced this approach, often leading to courts declaring patents invalid when they target abstract ideas without inventive concepts.
Despite these strict post-Alice decisions, investments in software R&D have surged, suggesting that such rulings haven’t stifled innovation within this sector. These judgments emphasize how critical it is for technological advances to be precisely reflected in patent claims when seeking intellectual property protection.
Distinguishing Between Reciting and Involving Abstract Ideas
The United States Patent and Trademark Office (USPTO) makes a clear distinction between claims that explicitly include an abstract idea as a fundamental component, compared to those that simply use or base themselves on an abstract idea without integrating it within the actual language of the claim. This difference is essential for determining whether claims with mere references to abstract ideas can qualify for patent eligibility based on their practical implications and uses. Claims that aren’t properly integrated into a practical application may be considered patent ineligible subject matter under the standards that the Alice decision and subsequent case law set.
Claims don’t account for mental processes if they include limitations that can’t feasibly be executed within the human mind. The USPTO separates claims that directly cite an “abstract idea” from those which merely associate with or derive from such an idea. This separation helps in evaluating both the inventive concept and establishing patent qualification, especially when examining claims that target specific implementations. These types of judicial exception-based claims cite additional elements that contribute to their constraints.
Making this distinction plays a crucial role in crafting applications that can claim patent-eligible status by allowing inventors to show technological advances and tangible uses, thereby fulfilling the necessary requirements.
Implications of the Supreme Court’s Alice Decision
The Supreme Court’s concern regarding the Alice/Mayo test centers on avoiding the monopolization of essential abstract ideas, which might hurt innovation. The ruling from Alice emphasizes that patents should enhance public knowledge rather than limit it with overly broad claims. The Alice decision has significantly influenced the patent system by shaping how courts interpret the patent statute, particularly regarding the eligibility criteria for software and computer-implemented inventions.
Since the court decided Alice, patent filings for business-method software have decreased noticeably. This trend hasn’t negatively affected venture capital investments within the software sector. Studies show that not having certain patents after Alice didn’t hurt positive business achievements such as acquisitions or initial public offerings (IPOs) in this field. Additionally, under the Alice framework, examiners often scrutinize claims that target a law of nature and may reject them if they merely apply a natural law without an inventive concept.
These insights suggest that securing patents could have costs that exceed their advantages and requires reconsideration of their importance specifically concerning software. Meanwhile, some entities continue efforts to revise patent law that could potentially weaken the outcomes that Alice dictated and thereby increase chances for more abstract concepts to be patented, possibly escalating disputes over patent infringement within the world of patents.
Machine-or-Transformation Test for Software Claims
The machine-or-transformation test determines the patentability of a process by checking whether it’s tied to a specific machine or causes an alteration in an article’s condition. The Supreme Court has indicated that while this test serves as a valuable tool, it shouldn’t be considered the sole criterion for establishing process patent eligibility. Meeting the requirements of the machine-or-transformation test can help demonstrate that a claim qualifies as a patent eligible application, as it may provide the inventive concept needed to transform an abstract idea into patent-eligible subject matter under the Alice/Mayo framework.
What exactly qualifies as ‘a particular machine’ and how much ‘transformation’ is required for something to be eligible for patent protection remains uncertain. Nevertheless, despite these ambiguities, the machine-or-transformation test offers an important guideline when assessing software-implemented inventions.
By understanding this test, inventors become better equipped to craft claims that reflect technological innovation and real-world utility—enhancing their prospects of meeting the standards that Alice/Mayo sets out and ultimately obtaining patent protection.
Strategies for Drafting Patent Eligible Software Claims
Crafting claims for software patents that meet eligibility requirements demands a focused approach that highlights technological progress and practical use cases. Based on extensive experience, the recommendation is to aim for developing solutions with concrete effects, steering clear of proposals that simply rearrange current data. Such an approach guarantees deeper integration of claims with computer technologies, focusing on particular software functions or hardware capabilities.
When drafting, it’s crucial to focus on patent eligible inventions by ensuring claims describe a patentable invention—one that constitutes a specific, technical improvement rather than an abstract idea, natural phenomenon, or routine application. Attorneys should avoid framing overly broad or frequently rejected claim groups, especially those that the USPTO associates with Section 101 rejections.
Stating specific technical benefits is essential in establishing software distinctiveness. Effective practice involves counteracting any ‘abstract idea’ objections by demonstrating how the invention improves upon existing computer functionality. To strengthen patent applications, introducing various independent process and method claims that cover diverse ranges of applicability while documenting incremental improvements as part of these additional claim elements within the submission proves beneficial.
Engaging proactively with patent examiners to explain technical specifics can lead to more precise implementation of claimed features during examination procedures. Through these concerted efforts, attorneys can create strong defensive positions for submissions ensuring they withstand scrutiny and meet criteria for patent eligibility.
However, patenting software remains challenging due to evolving legal standards, such as the Alice decision, which require applicants to clearly demonstrate that their invention qualifies as a patentable invention and meets the requirements for patent eligible inventions, rather than being an abstract idea or routine implementation.
Current USPTO Leadership Perspective on AI Patents
USPTO Director Kathi Vidal has emphasized the agency’s commitment to balancing innovation and clarity: “The USPTO remains committed to fostering and protecting innovation in critical and emerging technologies, including AI… [This] guidance update…will provide further clarity on evaluating subject matter eligibility of AI inventions while incentivizing innovations needed to solve world and community problems.”
Director Vidal has also stressed that the patent system welcomes AI-assisted inventions, provided a human is in the loop. She has noted that using AI tools in invention is becoming common and should be “encouraged” rather than feared. However, she has warned of potential challenges with AI-generated outputs creating a flood of prior art, which could impact the ability to patent some inventions if novelty and non-obviousness become harder to establish.
Crucially, USPTO officials have stated that the Alice/Mayo test applies equally to AI—AI inventions aren’t excluded from patents, nor do they receive special treatment. The focus remains on what inventors claim. The 2024 guidance explicitly states that the manner in which someone makes an invention (even if via AI) “doesn’t impact subject matter eligibility”; examiners evaluate an AI-assisted invention like any other, based on the claim’s content and improvements it provides.
Summary
Understanding the intricacies of the Alice/Mayo test is crucial for obtaining patent protection in the realms of software and AI. It’s important to understand this two-step analysis, figure out what constitutes abstract ideas, and establish inventive concepts. Inventors can elevate their abstract ideas into inventions that qualify for patents by concentrating on tangible applications and technological innovation.
The recent developments from 2024-2025, including the Federal Circuit’s Recentive decision and the USPTO’s comprehensive AI guidance with Examples 47-49, provide clearer roadmaps for navigating patent eligibility challenges. These examples demonstrate that specificity and technical application matter—AI or software-related claims must do more than describe abstract algorithms or data processing; they should emphasize how the invention improves technology or achieves tangible results.
In practice at Thompson Patent Law, proprietary techniques for preemptively addressing Alice rejections have proven effective in enhancing success rates by 25-50%, typically resulting in stronger patents that examiners allow through first or second office actions rather than prolonged prosecution. This approach not only saves inventors significant time and resources but also produces more robust intellectual property protection.
In an era where both software and AI are rapidly advancing, keeping up with criteria for patent eligibility becomes increasingly essential. Using strategic methods that build on a thorough understanding of these guidelines will enable inventors not only to secure protection around their creative works, but also make meaningful contributions towards technological advancement.
Frequently Asked Questions
What is the Alice/Mayo test?
The Alice/Mayo test plays a crucial role in determining the patent eligibility of inventions, focusing on whether they possess an inventive concept that goes beyond a mere abstract idea. This examination helps protect the recognition and protection of creative endeavors.
Why is the Supreme Court’s Alice decision significant?
The Alice decision by the Supreme Court has had a profound impact on patent law, as it determined that specific software advances are considered abstract ideas and thus don’t qualify for patent protection. By doing so, this ruling promotes innovation and competition within the technology sector by ensuring that overly general notions can’t be patented.
How can AI inventions qualify for patent protection?
Inventions involving artificial intelligence can qualify for patent protection when they convert conceptual ideas into practical applications that demonstrate concrete usefulness and distinct technological progress. By fulfilling these requirements, inventors can successfully protect their intellectual property rights.
What are some examples of technological improvements in AI inventions?
Technological improvements in AI inventions are revolutionizing the field with enhanced computer vision, more efficient data processing, and novel neural network architectures. These advances unlock new possibilities and drive innovation.
What strategies can be used to draft patent-eligible software claims?
To effectively draft patent-eligible software claims, emphasis should be placed on inventions that deliver tangible results while avoiding generic descriptions. Clearly defining technical advantages, using multiple independent claims, and documenting improvement steps, while engaging with examiners, strengthens applications.
