[Explained Through Case Studies] Can AI Agents Be Patented? Patent Case Studies and Examination Practices in Japan, the U.S., and Europe | Supervised by a Patent Attorney

Table of Contents

1. What Are AI Agent Patents? Basics Before Reviewing Case Studies
2. Three Perspectives for Analyzing AI Agent Patents
3. [Japan/JPO] Case Studies of AI Agent Patents
4. [U.S./USPTO] Case Studies on AI Agent Patents
5. [Europe/EPO] Case Studies of AI Agent Patents
6. Comparison of Examination Practices in Japan, the U.S., and Europe (Quick Reference Chart)
7. Learning from Case Studies | 5 Key Points for Successful Patent Grant
8. Frequently Asked Questions (FAQ)
9. Reference Sources

JPO Case: Granted

A case where “prediction accuracy was significantly improved” by a new input variable (estimation of hydroelectric power generation)

While a configuration that merely replaced a conventional regression model with a neural network was deemed to lack inventive step, a configuration that added “river water temperature” as an input variable to account for snowmelt inflow—thereby significantly improving prediction accuracy—was judged to possess inventive step. The key lies in technically meaningful innovations regarding input features and training data.

JPO Case Study: Rejection (NG)

Case of Simply Replacing Human Work with AI (Calculating Cancer Severity)

An approach that merely replaced the manual calculation of cancer probability based on blood markers—previously performed by physicians—with a pre-trained neural network was deemed to lack inventive step, as it was considered “merely the automation of human tasks using AI.”

JPO Case Study: 2024 · LLM

Inventive Step in Configurations Using Generative AI (LLM)

While a system that automatically generates answers by inputting questions into an LLM (such as automated customer service responses) was denied inventive step, a specific process that extracts multiple keywords from relevant documents to generate prompts and produce more appropriate text was granted registration on the grounds that it provided a significant effect.

Actual Patents | Japan

JP 7282070 (Mitsubishi Electric) | “Compressed Data” for Neural Networks

A patent regarding data that compresses the configuration information of a neural network through quantization (registered in 2023). This is an example of securing intellectual property rights for “data structures” in the AI field.

Actual Patents | Japan

JP 7177608 (Komatsu) | Pre-trained Position Estimation Model for Construction Machinery

A system patent (registered in 2022) using a pre-trained model to estimate the position of a hydraulic excavator’s working equipment based on camera images. This is an excellent example of securing rights not only for the system and method but also for the manufacturing method of the pre-trained model and the training data, serving as a reference for autonomous machine control (an area adjacent to AI agents).

Actual Patents | U.S.

US 10,452,978 (Google) | Transformer Patent

A patent (granted in 2019) for a neural network based on the self-attention mechanism, corresponding to the paper “Attention Is All You Need.” This architecture forms the foundation of all modern LLMs and AI agents.

Existing Patent | U.S.

US 11,922,144 (OpenAI) | External API Integration (Tool Utilization)

A patent (registered in 2024) in which an LLM reads an API schema (manifest) and generates function calls to external tools (such as shopping, databases, and email) without the need for retraining. This is a core patent for “AI agents,” corresponding to ChatGPT’s plugins and function calls.

EPO Case: Rejection Not Accepted

T 0702/20 (Mitsubishi Electric) | Sparsely Connected Neural Network

Regarding a neural network structure that uses error-correcting codes to create sparse connections between layers, the Board of Appeal acknowledged that it was “novel and non-trivial” but rejected the application on the grounds that it merely defined a class of mathematical functions (an exclusion).This is an important case demonstrating that an objective such as “preventing overfitting” alone is insufficient, and that it is difficult to obtain protection in Europe for improvements to core AI.

EPO Case: Key Ruling

G 1/19 (Enlarged Board of Appeal, 2021) | Pedestrian Crowd Simulation

Regarding computer-based simulations of pedestrian crowd movement, the Enlarged Board of Appeal ruled that “computer-implemented simulations are assessed using the same criteria as other software inventions” and that “numerical output can constitute a technical effect.” This provides guidance for simulation and planning-type AI inventions.

Actual Patents | Europe

EP 3398117 (DeepMind) | Neural Network Extended with External Memory

A European patent (registered in 2023) for an architecture that combines a neural network with external memory (storage). This registered case is directly linked to the “memory” function of AI agents, which retain information and utilize it for subsequent actions.

Common Essence: What the three regions have in common is not “what AI achieves (business idea),” but rather the need to specifically describe “how to technically achieve it.” This single point determines the success or failure of AI agent patents.

Patenting AI agent technology—start by consulting with us.

Patent attorneys with expertise in the IT and software fields provide comprehensive support—from technical consultations and prior art searches to patent prosecution strategies in each country. We offer a free initial consultation.

Q. Can AI agents be patented?

A. Yes, they can. While the inference algorithms of AI agents themselves are mathematical methods, if they are described as systems or methods that specifically implement information processing using hardware resources such as computers, they may be eligible for patent protection in Japan, the U.S., and Europe.In fact, numerous foundational technologies for AI agents have been patented, such as Google’s Transformer patent (US10,452,978) and OpenAI’s tool integration patent (US11,922,144).

Q. Can you obtain a patent based solely on the design of a prompt?

A. In reality, it is difficult to do so. The prompt text itself is often regarded as a “human instruction (presentation of information),” and there is a risk that it will not be deemed an invention.In a 2024 case from the Japan Patent Office, a configuration that simply inputs a question into an LLM to generate a response was found to lack inventive step. On the other hand, the likelihood of obtaining a patent increases if the method is described as an information processing process that dynamically generates and synthesizes prompts based on context.

Q. Which region—Japan, the U.S., or Europe—is the easiest to obtain a patent in?

A. While it’s difficult to generalize, the registration requirements for software inventions are generally assessed as follows: “Japan is relatively lenient, while Europe (EPO) has the strictest requirements regarding technical contribution.”While the U.S. standards became stricter following the Alice decision, the July 2024 AI Examination Guidelines (Examples 47–49) have increased predictability in practice. In any of these countries, explicitly demonstrating that “a technical problem is solved by technical means” is key.

Q. Are there any well-known examples of AI agent patents?

A. Representative examples include Google’s patent (US10,452,978) for “Transformer,” which forms the foundation of modern LLMs,OpenAI’s patent on external API integration (US11,922,144), which corresponds to ChatGPT’s plugins and function calls; and DeepMind’s patent on external memory-extended neural networks (European EP3398117).In Japan, patents such as Mitsubishi Electric’s patent on neural network compression (JP7282070) and Komatsu’s patent on pre-trained models for construction machinery (JP7177608) have also been registered.

Q. Can I file a patent application even after publishing the technology in a paper or on GitHub?

A. As a general rule, once a technology is made public, it loses novelty and cannot be patented. Japan has an “exception to loss of novelty” (Article 30) system that provides relief under certain conditions, but the requirements vary by country, so it is not a universal solution. Given the rapid pace of disclosure in the AI industry, it is extremely important to complete the patent application before publishing a paper, releasing open-source software, or issuing a press release.

Q. Should I consult a patent attorney regarding inventions involving AI agents?

A. We strongly recommend it. Patenting AI agents requires a high level of expertise to extract “patentable technology” from systems that tend to be black boxes and to design claims (scope of protection) in accordance with the examination standards of each country. By consulting with a patent attorney well-versed in the IT and software fields, you can build a strong patent portfolio that is difficult for competitors to circumvent.