New Study: AI Patents Face Higher Invalidation Rates Under 101

Estimated reading time: 8 minutes

If you are working with artificial intelligence, you may assume that building something novel automatically makes it patentable. In practice, that is not always how things play out.

A recent study by Amy Semet, Associate Professor of Law at the University at Buffalo School of Law, published through the IP Policy Institute, suggests that AI-related patents are being invalidated under Section 101 at notably higher rates than comparable non-AI patents. The study examined AI patents asserted in U.S. district court litigation from 2000 through 2025, using the USPTO’s Artificial Intelligence Patent Dataset to classify AI inventions across several confidence thresholds.

To make sense of this, it helps to step back and understand what Section 101 is, why it matters, and how it is shaping the landscape for software patent filings.

What Is Section 101 in Plain English

Section 101 is part of U.S. patent law that defines what kinds of inventions are eligible for patents. In simple terms, it asks a threshold question:

Is this the type of thing that can be patented at all?

Certain categories are excluded from patent eligibility, even if they are new and useful. These include:

• Abstract ideas
• Laws of nature
• Natural phenomena

For software and AI, this becomes tricky. Many AI systems are built on mathematical models, algorithms, and data transformations, which can sometimes be viewed as abstract ideas.

That is where the challenge begins.

Why AI Patents Are Being Scrutinized More Closely

The study suggests that AI-related patents are more likely to run into Section 101 problems compared to other technologies. It found a clear and consistent pattern: when cases reached a contested merits outcome, AI-related patents were significantly more likely to be invalidated than similar non-AI patents, and that higher invalidation rate was driven mainly by Section 101 subject-matter eligibility rather than obviousness under Section 103.

The Line Between “Abstract Idea” and “Technical Innovation”

AI systems often involve steps like training a model, processing inputs, and generating outputs. At a high level, that can look similar to abstract decision-making or data processing.

Examiners and courts are trying to distinguish between:

• A general idea, such as “using AI to analyze data”
• A specific technical solution, such as a new way of structuring or improving a model

If a patent leans too heavily toward the general idea, it may be seen as ineligible.

Broad Claims Can Work Against You

In fast-moving fields like AI, it is tempting to draft broad claims that cover many possible applications. But broad claims can also raise red flags under Section 101.

They may be interpreted as trying to monopolize an abstract concept rather than protect a specific implementation.

What “Invalidation” Actually Means

The term “invalidation” can sound dramatic, but it is important to understand it correctly.

A patent can be challenged and found invalid if it does not meet legal requirements, including Section 101. This can happen:

• During examination at the USPTO
• In post-grant proceedings
• During litigation

For AI patents, the concern raised by the study is that Section 101 is playing a larger role in these outcomes than in other technology areas.

The study also suggest that AI patents may face pressure from multiple directions. According to the study discussion, 23.6% of AI patents asserted in district court were also challenged in PTAB validity proceedings, compared with 11.9% of asserted non-AI patents. In other words, litigated AI patents appeared to be challenged at the USPTO at about twice the rate of non-AI asserted patents.

That does not mean AI patents cannot succeed. It does mean the margin for error may be smaller.

The study also reported that AI patent disputes are more likely to be screened out early through motions to dismiss or judgments on the pleadings, rather than reaching trial-intensive stages. That matters because Section 101 issues are often raised early, before the case gets deep into factual development.

How This Affects Software Patent Strategy

If you are considering a software patent or computer software patent involving AI, this trend should influence how you approach the process.

Focus on the Technical Details

One of the most practical takeaways is the importance of clearly describing the technical aspects of your invention.

Instead of framing your invention as “using AI to do X,” it helps to explain:

• How the model is structured or trained
• What technical problem is being solved
• What specifically improves compared to existing approaches

The more concrete and technical your description, the easier it is to move away from the “abstract idea” category.

Be Thoughtful About Claim Scope

There is always a balance between broad protection and defensibility. In AI, leaning too far toward broad, high-level claims can increase risk under Section 101.

A more measured approach often involves:

• Defining specific implementations
• Including meaningful technical limitations
• Avoiding overly generic language

This does not guarantee success, but it can improve positioning.

Expect a More Involved Examination Process

“Prosecuting a patent” refers to the back-and-forth process with the USPTO after filing. For AI-related applications, that process may involve more detailed eligibility discussions.

You may see:

• Additional rejections based on Section 101
• Requests for clarification of technical features
• More emphasis on how the invention differs from abstract concepts

Planning for that upfront can make the process less frustrating.

The Role of Patent Searching and Landscape Awareness

As scrutiny increases, understanding the existing patent landscape becomes even more valuable.

Tools like a USPTO patent search or broader patent searching databases can help you get a sense of:

• How similar inventions are described
• What kinds of claims have been allowed
• Where potential risks may arise

You might also look at:

• US patent search by company to see how competitors are drafting applications
• US patent office search systems to review published filings
• general patents search tools for patterns in examiner behavior

This is not just about avoiding duplication. It is about learning how to frame your own invention more effectively.

A Quick Note on “Abstract Ideas” in Practice

One of the most confusing parts of Section 101 is that “abstract idea” does not have a simple, fixed definition.

In practice, the analysis often comes down to questions like:

1. Is the claim directed to a general concept?
2. If so, does it add enough technical detail to transform that concept into a patent-eligible invention?

For AI, the second step is where many applications succeed or fail.

Adding concrete, technical elements can make a meaningful difference. Leaving them out can make the invention look like a high-level idea rather than a specific solution.

What This Means for Founders and Teams

If you are building AI products, this trend does not mean you should avoid patents. It simply means you should approach them with clearer expectations.

A few practical considerations:

• Document your technical decisions carefully, especially what makes your approach different
• Think early about how your system improves technology, not just business outcomes
• Use tools like the USPTO public patent search or Google Patents to stay informed about similar filings
• Recognize that outcomes depend heavily on how the application is written and examined

Working with a qualified US patent agent, patent attorney services provider, or software patent lawyer can also help translate your technical work into language that aligns with patent eligibility standards.

The Bigger Picture for AI Innovation

The higher rate of Section 101 invalidations for AI patents reflects a broader tension in the patent system.

On one hand, there is a desire to encourage innovation and protect new ideas. On the other, there is caution about granting overly broad rights that could limit competition.

AI sits right in the middle of that tension.

It is powerful, fast-moving, and often built on foundational mathematical concepts. That makes it both valuable and difficult to fit neatly into existing legal frameworks.

As a result, the rules are still being interpreted and applied in real time.

Final Thoughts on Section 101 and AI Patents

The key takeaway is not that AI patents are doomed. It is that they are being examined with particular care under Section 101.

For anyone considering a filing, understanding this landscape can help you make better decisions about how to describe and protect your invention.

A thoughtful approach to a software patent, combined with awareness of trends seen in USPTO patent search results and examination patterns, can improve your chances of navigating this evolving area successfully.

The recent data reinforces that point. If AI patents are more likely to face early eligibility challenges, then the drafting strategy cannot treat Section 101 as an afterthought. The application should be built from the start around a specific technical improvement, supported by enough implementation detail to show that the invention is more than a broad idea of applying AI to a problem.

The goal is not to eliminate risk. It is to approach the process with clarity, technical depth, and realistic expectations.