How AI patents are changing innovation and what it means for creators

01The current landscape of AI patent filings

A patent is a type of intellectual property that gives its owner the legal right to exclude others from making, using, or selling an invention for a limited period of time, in exchange for publishing an enabling disclosure of the invention. It offers a bargain between society and inventor: for a limited time, the inventor gets exclusive rights; in return, the public gets the knowledge. AI patent filings have grown rapidly in recent years, with thousands of applications submitted annually across major patent offices worldwide.

The World Intellectual Property Organization reported a surge in AI-related patent families filed under the Patent Cooperation Treaty. Between 2020 and 2026, filings in AI-related categories grew at roughly 30 percent annually, outpacing nearly every other technology class. China, the United States, and South Korea account for the majority of these filings, with Chinese applicants alone responsible for a substantial share of global AI patent families.

Artificial intelligence is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. As AI has moved from research labs into commercial products, companies have raced to patent the underlying methods, from neural network architectures to training pipelines and deployment infrastructure.

02What can be patented when AI is involved

The core question is what, exactly, can be patented when AI is involved. Patent law has traditionally required that an invention be new, useful, and non-obvious to a person having ordinary skill in the art. AI inventions must meet these same criteria, but the application of these standards to machine learning systems raises novel questions. Is a neural network architecture a patentable invention, or is it an abstract mathematical concept excluded from patentability?

In the United States, the Alice framework requires that patent claims involve something more than an abstract idea implemented on a computer. AI patents that merely claim the application of a known algorithm to a known problem may be invalidated as abstract. Patents that claim specific improvements to computer functionality, such as novel training methods or hardware acceleration, are more likely to survive.

In Europe, the European Patent Office requires that an invention have a technical character. AI claims that solve a technical problem, such as improving image recognition accuracy or optimizing power consumption in a data center, may qualify. Pure business methods implemented with AI, however, face significant hurdles. The distinction between technical and non-technical applications of AI is one of the most contested areas in patent law.

03The difference between AI as tool and AI as inventor

One of the most fundamental questions is whether an AI system can be named as an inventor on a patent. The DABUS cases, litigated in multiple jurisdictions, tested this question directly. Stephen Thaler filed patent applications naming his AI system, DABUS, as the inventor of two inventions. Patent offices and courts in the United States, United Kingdom, and Europe rejected the applications, holding that an inventor must be a natural person.

The distinction matters because it determines who owns the patent. If an AI is the inventor, the patent might belong to no one, or to the owner of the AI system, creating legal uncertainty. The current consensus across jurisdictions is that AI can be a tool used by a human inventor, but cannot itself be an inventor. The human who conceives of the invention and directs the AI in its development is the inventor.

Innovation is the practical implementation of ideas that result in the creation or improvements of goods or services. When AI is used as a tool in the innovative process, the human who identifies the problem, designs the AI approach, and recognizes the solution remains the inventor. This framework preserves the incentive structure of the patent system while acknowledging the growing role of AI in research and development.

04How patent offices are adapting

Patent offices worldwide are adapting to the surge in AI patent filings. The US Patent and Trademark Office has established an AI and emerging technologies working group to examine AI-related patent applications and develop examination guidance. The European Patent Office has issued guidelines on how to assess the inventive step of AI inventions, focusing on whether the claimed invention provides a technical solution to a technical problem.

The Japan Patent Office and the Korean Intellectual Property Office have also published examination guidelines for AI-related inventions. These guidelines address issues such as the sufficiency of disclosure, which requires that a patent application describe the invention in enough detail for a skilled person to reproduce it. For AI inventions, this may require disclosing training data, model architecture, and hyperparameters.

The challenge for patent offices is balancing access to patent protection for AI innovation against the risk of granting overly broad patents that stifle competition. Some AI patents claim fundamental techniques that could be applied across many industries, and granting such patents to a single entity could create bottlenecks. Patent offices are developing expertise in AI technology to make better-informed examination decisions.

05The impact on startups vs big tech

The AI patent landscape is characterized by a significant imbalance between large technology companies and startups. Major technology companies hold vast portfolios of AI patents, accumulated through years of research and aggressive filing strategies. These portfolios serve both defensive and offensive purposes: they protect the company's products from infringement claims and can be used to challenge competitors or extract licensing fees.

Startups face a different reality. Filing a single patent application can cost tens of thousands of dollars in attorney fees and examination costs, and building a patent portfolio that provides meaningful protection requires multiple filings across multiple jurisdictions. Many startups choose to invest their limited resources in product development rather than patent filing, leaving them vulnerable to infringement claims from larger competitors.

The result is a patent landscape that may favor incumbents over new entrants. Some have argued for reforms such as lower filing fees for small entities, faster examination tracks for AI patents from startups, or even a limited exemption from patent infringement for early-stage companies. Whether such reforms will be adopted remains uncertain, but the tension between patent protection and startup innovation is a growing policy concern.

06What the courts are ruling

Courts in multiple jurisdictions are grappling with the legal questions raised by AI patents. In the United States, the Federal Circuit has refined the boundaries of patentable subject matter for AI inventions through a series of decisions. The trend has been toward requiring specific, technical implementations rather than abstract claims to AI functionality.

In Europe, the Boards of Appeal of the European Patent Office have issued decisions clarifying the technical character requirement for AI inventions. A key principle is that the use of AI to solve a technical problem, such as controlling a manufacturing process or optimizing a communication network, can provide the technical character needed for patentability. Using AI to solve a business or administrative problem generally cannot.

Litigation over AI patents is also increasing as commercial stakes grow. Companies are asserting AI patents against competitors in fields ranging from autonomous vehicles to medical diagnostics. The outcomes of these cases will shape the practical value of AI patents and influence future filing strategies. The courts are effectively defining the metes and bounds of AI patent rights on a case-by-case basis.

07How innovators should protect AI inventions

For innovators seeking to protect AI inventions, the current landscape suggests a multi-layered strategy. First, patent applications should focus on specific technical implementations rather than broad conceptual claims. Claims that describe a novel neural network architecture applied to a specific technical problem, with measurable improvements over prior approaches, are more likely to survive examination and litigation.

Second, innovators should consider the timing of patent filings. The United States operates on a first-to-file system, meaning that the first person to file a patent application for an invention gets the patent rights, regardless of who first invented it. This makes early filing important, but filing too early, before the invention is fully developed, can result in an application that lacks sufficient disclosure.

Third, patent protection should be part of a broader intellectual property strategy that includes trade secrets, copyrights, and contractual protections. Some AI innovations may be better protected as trade secrets, particularly those that are difficult to reverse engineer, such as training data and internal model parameters. A balanced approach that uses patents for externally visible innovations and trade secrets for internal improvements can provide comprehensive protection.