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If you’ve got an artificial intelligence invention, you might be wondering if you can actually patent it. The short answer is yes, in many cases, you can. But the process is more nuanced than filing a standard utility patent, and getting it wrong early can cost you protection that matters later.
At Gearhart Law, we have worked with inventors, startups, and growing companies from our office in Summit, NJ, for decades, guiding them through the process of figuring out what is worth protecting and how to do it right. As an AI patent law firm that stays current with how the USPTO approaches machine learning patents and software patent eligibility, we understand both the technology and the legal landscape well enough to make a real difference in the outcome.
This article walks through what you need to know about patenting artificial intelligence inventions in the United States, where the common pitfalls are, and what steps to take if you are ready to move forward.
Artificial Intelligence Inventions the USPTO Will and Will Not Protect
The U.S. Patent and Trademark Office (USPTO) does not grant patents on abstract ideas. That rule sits at the center of almost every AI patent eligibility conversation, and it trips up a lot of applicants who come in without a clear strategy.
If your invention is essentially a mathematical formula, a general concept, or a method that could be performed in someone’s head, the patent office is likely to reject it. AI inventions described too broadly, without tying them to a concrete technical application, often fall into this category.
What the USPTO will consider is an AI-based invention that produces a specific, real-world technical result. The invention needs to do something tangible, not just process information in the abstract. Examples of AI inventions that may qualify for patent protection include:
- A machine learning patent covering a model that improves the speed or accuracy of a specific technical process
- A novel neural network architecture that produces measurably different results from existing approaches
- An AI system integrated with hardware to perform a defined function, such as medical imaging analysis or manufacturing quality control
- A training method or data pipeline that solves a concrete technical problem in a new way
- Software where the AI improvement is to the computer system itself, not just the task it is performing
Working with a software patent attorney who understands this distinction early in the process helps you frame your invention correctly from the start, rather than trying to fix a rejection after the fact.
The Alice Problem and Why Every AI Applicant Needs to Know About It
If you have started researching AI patent applications, you have likely come across references to “Alice rejections.” Here is what that means and why it matters.
In 2014, the Supreme Court decided Alice Corp. v. CLS Bank International, a case that established a two-step test for determining whether software and computer-implemented inventions are patent-eligible. The USPTO applies this test aggressively, and AI patent applications are squarely in its scope.
Step one asks whether the claim is directed to an abstract idea. If yes, step two asks whether there is something significantly more present, an inventive concept that transforms the abstract idea into something the patent system will protect.
Many AI patent applications fail at step two because they describe what the AI does without explaining how it achieves a specific technical improvement. If your application reads like “apply machine learning to problem X,” expect a rejection.
The fix is not to abandon the application. It is important to draft the claims correctly from the beginning. That means describing the concrete technical outcome, the specific method by which the AI achieves it, and why that approach is not obvious to someone working in the field. A software patent attorney who has navigated Alice rejections before knows how to build that case directly into the application itself.
Why a Patent Search Has to Come Before Filing
Before you file anything, you need to know two things: whether your invention is patentable, and whether it steps on someone else’s patent.
A thorough patent search and literature review address both. On the patentability side, it gives your attorney a clear picture of the prior art landscape, what has already been published, filed, or issued in your technology area. That knowledge shapes how the application is drafted, and a stronger understanding of prior art leads to stronger, better-targeted claims.
On the freedom-to-operate side, you need to know whether launching your product puts you in conflict with an existing patent holder. You can run a preliminary search using Google Patents or the USPTO’s patent search tool, but a professional search goes significantly deeper and is interpreted in the context of your specific claims.
Here is the reality: if you put a product on the market that infringes a third-party patent, it does not matter whether a human or an AI wrote the underlying code. You are the infringer. Finding out three years after launch, when someone is demanding royalties or seeking an injunction to block your product entirely, is a situation a patent search upfront could have helped you avoid.
At Gearhart Law, we walk every client through both of these analyses before recommending a filing strategy. It is the responsible starting point, and it protects you down the road.
Can AI Be Listed as the Inventor on a Patent Application?
This question has gone from theoretical to genuinely pressing over the last few years, and U.S. law has been consistent in its answer.
Under current U.S. patent law, inventors must be natural persons. The USPTO and the Federal Circuit have both confirmed this, including in the well-known DABUS cases, where an AI system was listed as the named inventor on a series of applications. U.S. courts declined to extend inventorship to AI, and that position holds today.
What this means for your AI patent application: if your team used AI tools during development, the human contributors who made the meaningful, creative, and technical decisions are the inventors. The AI is a tool, not a co-inventor.
Getting inventorship right matters more than most people realize. Incorrectly naming inventors creates legal vulnerabilities that can be used to challenge a patent’s validity down the road.
Building a Layered Intellectual Property Strategy for Your AI Product
One patent rarely protects an AI product on its own. The companies that build durable intellectual property protection around their technology think about IP as a portfolio, not a single filing.
A well-rounded strategy for protecting an AI product might include:
- Utility patents covering the core system or algorithm as implemented
- Method patents on specific training processes or inference pipelines
- Continuation applications to capture improvements as the product evolves
- Trade secret protection for elements of the model that are difficult to reverse-engineer
- Copyright protection for original code and, in some cases, model outputs
- Trademark registration to protect the brand identity built around the product
The goal is layered protection. No single layer is perfect on its own. However, together they make it significantly harder for a competitor to copy what you have built without consequences.
This is especially relevant for companies working in life sciences, medical devices, and software, where AI is being embedded into products that sit at the intersection of multiple IP categories. An AI patent law firm can help you determine which tools apply to your specific situation and how to sequence filings for maximum coverage.
From Application to Approval: How the Process Works
For most AI inventions, the process starts with a provisional patent application. A provisional secures your priority date, which is critical in the U.S. first-to-file system. It also gives you 12 months to refine the invention before the formal application is due.
After the formal application is filed, the USPTO assigns it to an examiner. For AI and software patent applications, examination typically takes two to three years, though this varies by technology area and workload. During examination, the examiner may issue office actions, written rejections, or requests for clarification that your attorney responds to on your behalf.
The examination process is not just administrative back-and-forth. It is where the claim scope gets negotiated. How your attorney responds to office actions directly affects how broad or narrow your final patent protection will be. Having a software patent attorney who has been through this process many times, and who knows how to respond to an Alice rejection and argue for broader claims, gives you a meaningful advantage at this stage. It is one of the clearest cases where the right legal guidance translates directly into a stronger outcome.
Ready to Protect What You Have Built?
AI patent law is not a plug-and-play process. It requires understanding the technology, knowing the current patent eligibility landscape, and drafting applications that hold up under scrutiny. If you are building something in AI and have not yet spoken with an NJ patent attorney about protecting it, the best time to start is before you file and before you launch.
At Gearhart Law, we offer a free half-hour consultation to talk through what you have built and what intellectual property protection might look like for your situation. As an AI patent law firm working with clients across New Jersey and nationwide, we are ready to help you figure out the right path forward.
Call us at 908.273.0700 or send us a message.
Frequently Asked Questions about Protecting Your Artificial Intelligence Invention
1. Can you patent an AI algorithm?
Not the algorithm in the abstract. But if the algorithm is implemented in a specific way that produces a concrete technical result, a machine learning patent may be possible. The claim has to be grounded in a real application, not just describe the underlying math or logic. A patent attorney can help you evaluate whether your specific implementation qualifies for patent protection.
2. What is an Alice rejection, and how do you get past one?
An Alice rejection means the examiner has determined that your claim is directed to an abstract idea without enough additional inventive content to make it patent-eligible. Getting past it requires demonstrating that your invention produces a specific technical improvement. The Alice Corp. v. CLS Bank decision is the controlling authority here, and strong claim drafting from the start is the best way to avoid the issue entirely.
3. Does it matter that AI helped write the code behind my invention?
For inventorship purposes, what matters is who made the key creative and technical decisions, and that must be a human being under current U.S. law. For patent infringement purposes, using AI to write code does not protect you from liability if the resulting product infringes a third-party patent.
4. How long does an AI patent application take?
From filing a formal application, the USPTO typically takes two to three years to examine AI and software patent applications. Filing a provisional application first locks in your priority date and gives you 12 months before the formal application is due. You can track your application status through the USPTO’s Patent Center.
5. What if a competitor already has something similar to my AI invention?
Similar is not the same as identical. A patent search identifies what the prior art actually covers so your attorney can draft claims around the genuinely novel aspects of your invention. It also surfaces any freedom-to-operate issues that need to be addressed before launch.
6. Do I need to be located in New Jersey to work with Gearhart Law?
No. We work with clients across the country on patent, trademark, and copyright matters. Call us at 908.273.0700 or visit gearhartlaw.com to schedule a free consultation from wherever you are located.