This technology holds the potential to transform every business, and a fierce global race to develop it is underway.To protect your company’s innovative AI agent technology from imitation, the importance of “filing a patent application” has never been greater. However, many engineers and executives are concerned about questions such as, “Are AI agents eligible for patents?” and “Can a patent be obtained simply by devising a clever prompt?”
In this article, a patent attorney with deep expertise in the AI field will provide a comprehensive explanation of the essential requirements for successfully filing a patent application for AI agents, specific examples of ideas that are likely to be patented, points to note when filing, and the reasons why you should choose a professional patent attorney. If you want to protect your company’s AI technology as strong intellectual property and gain a competitive edge in business, please be sure to read this article to the end.
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In conclusion, AI agent technology is eligible for patent applications, and patents can be obtained if the necessary conditions are met.
Under patent law, an “invention” is defined as “a creation of a technical concept utilizing the laws of nature.” While AI inference itself is a mathematical algorithm and, in principle, is not patentable, in Japanese patent practice, if that information processing is “specifically implemented using hardware resources (such as a CPU or memory),” it becomes eligible for a patent as a software-related invention.In other words, if an AI agent is described in the specification as a system that performs specific data processing on a computer, it will be recognized as eligible for a patent.
In traditional AI patents, the structure of training data and the architecture of neural networks were the primary subjects of patent protection. In contrast, today’s AI agents are predominantly based on existing large language models (LLMs). Consequently, rather than improvements to the model itself, the main focus of patenting is on the system configuration and processing flow—specifically, “how the LLM is utilized to build an autonomous system.”The ingenuity behind “how to make the AI move its ‘limbs’ through specific procedures” is the key to securing patent protection.
| Perspective | Traditional AI Patents | AI Agent Patents |
|---|---|---|
| Main Subject of Patent Protection | Training data structures and neural network architectures | System architecture and processing flows utilizing LLMs |
| Core of the Invention | Improvements to the Model Itself | Procedures and control logic for autonomous task execution |
| Points of Differentiation | Novelty of the Architecture | Innovative Approaches to “How to Make AI Move Its Limbs” |
To pass the Japan Patent Office’s examination and obtain a patent, the following three main requirements must be met:
Novelty means that, as of the filing date, the technology is unknown anywhere in the world. As a general rule, technologies for which detailed mechanisms have already been disclosed—such as through academic papers, open-source releases on GitHub, or the company’s own press releases—lose their novelty and cannot be patented.Although the AI industry moves at a rapid pace, it is extremely important to “complete the patent application before any information is made public.”
The biggest hurdle for AI-related patents is “inventive step.” This refers to a level of difficulty such that a specialist in the field would not readily conceive of the invention based on existing technology.An application for a “system that replaces customer support—which was previously performed by humans—with AI agents” would be deemed a mere business application of existing technology, and its inventive step would be denied. To claim inventive step, it is necessary to focus on technical challenges—such as “how the agent searches and filters the internal database to prevent hallucinations”—and the specific solutions to those challenges.
The patent system grants exclusive rights in exchange for disclosing an invention. Therefore, the specification must be detailed enough that “a person skilled in the art could build the same system upon reading it.”While AI inference processes tend to be black boxes, abstract descriptions such as “feeding data into the AI yields the optimal answer” will result in rejection. Advanced skills are required to describe, in a logical and concrete manner, what input data is used and under what conditional branching the API is called.
So, what kinds of technologies are likely to be recognized as having inventive step? Here are three approaches with a high likelihood of obtaining a patent.
The most distinctive feature of AI agents is their ability to break down abstract instructions into specific tasks and plan the order of execution. By ensuring the uniqueness of this planning logic, you can aim to secure a patent.“An information processing flow that, when an external API error occurs during task execution, does not simply stop but autonomously infers the situation, explores alternative approaches, and dynamically modifies (replans) the plan” has the potential to be a strong patent.
AI agents retain past interactions as memories and utilize them to inform their next actions. Additionally, RAG (Retrieval-Augmented Generation) technology, which enables the agent to provide responses based on the company’s own data, is indispensable.Rather than merely a search-augmentation mechanism, concepts such as a “memory management system that dynamically adjusts the weighting of retrieved past memories based on the user’s current emotions and the urgency of the task” or “an algorithm that autonomously regenerates queries and performs additional searches when the AI itself determines that search results are insufficient” are highly patentable.
Systems in which multiple AI agents with different roles (e.g., agents for requirements definition, coding, and testing) communicate and collaborate to complete a single large-scale task are a goldmine for patents.Good examples include a “protocol that automatically reaches consensus based on specific evaluation metrics when agents disagree” and a “feedback loop mechanism that dynamically changes the structure of coding prompts depending on the type of error discovered during testing.”
Tip for securing patent rights: What these examples have in common is the originality of their “autonomous decision-making and dynamic control logic.” Rather than simply listing functions, specifying “under what conditions and how the behavior changes dynamically” is the surest path to having your invention recognized as involving an inventive step.
Patent applications for AI agents have their own unique pitfalls. Filing without being aware of these can result in unnecessary costs.
Pitfall #1: An idea such as “fully automating reservation operations in the XX industry using an AI agent” is merely a business model and cannot be patented. To obtain a patent, you need a specific solution that answers the question, “How is this implemented as a system?” The processing procedures must be detailed to a level where an engineer can actually implement them.
Pitfall 2: The prompt itself—such as “Enter this instruction to get good output”—is often viewed as a mere “convention” expressed in human language, carrying a high risk of not qualifying as an invention under patent law.
As a countermeasure, rather than describing the prompt text itself, the scope of protection must be defined as an information processing procedure—specifically, “how the system dynamically generates and synthesizes prompts based on certain conditions and the user’s context, and sends them to the LLM.”
Pitfall #3: If you draft claims that are entirely dependent on the specifications of a specific external API (such as OpenAI), there is a risk that the patent will become unenforceable (falling outside the scope of protection) if you switch to a different LLM in the future. It is essential to clearly identify your company’s proprietary developments (core value) and adopt a strategy to secure patents based on universal concepts that are not dependent on specific technologies.
Patent applications related to AI agents are highly specialized. To secure strong patents that directly contribute to business success, it is absolutely essential to engage a patent firm (or patent attorney) with deep expertise in AI and software technology.
While developers may be able to describe the big picture—such as “we’ve created an amazing agent”—it is difficult for them to determine exactly which aspects of that creation are evaluable under patent law. Patent attorneys with expertise in AI use in-depth consultations to accurately identify and articulate the “patentable, unique algorithms and data flows” hidden deep within system architectures that tend to be treated as black boxes.
A patent will be rejected if its scope of protection (claims) is too broad, and if it is too narrow, competitors can easily circumvent it. Determining how much to abstract AI’s internal processing in the claims and where to describe it concretely requires a delicate balance—a strength unique to experts who have extensive experience examining numerous AI patents.We predict competitors’ imitation patterns and build a robust patent network based on higher-level concepts.
Filing for a patent (and having it published) is not always the best approach. In some cases, maintaining proprietary training data as “trade secrets (know-how)” within the company—rather than disclosing it—is the best way to preserve your competitive edge.Patent attorneys well-versed in the AI business will appropriately distinguish between what should be protected by patents and what should be kept confidential as know-how, proposing a comprehensive IP strategy that maximizes your company’s business value.
AI agents are an extremely important technology that will become the core of business competition across all industries in the future. If you postpone filing a patent application simply because “you’re not sure if it’s patentable,” you run the critical risk that competitors will secure patents first, preventing your company’s system from ever launching.
Implementing an IP strategy that incorporates patent applications from the very start of your development project is an absolute necessity for safeguarding your company’s market advantage and enhancing your corporate valuation in the eyes of investors.
Our firm employs patent attorneys with extensive practical experience in the IT and software fields who are well-versed in the latest AI patent trends. Drawing on our track record of successfully securing numerous patents, we provide comprehensive support to develop the optimal IP strategy to protect your company’s technological capabilities and business.From technical consultations and prior art searches to a free assessment of your chances of obtaining a patent, please feel free to take advantage of our free initial consultation.
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