Introduction
Artificial intelligence (AI) is transforming innovation across industries, challenging traditional intellectual property (IP) systems to adapt. As AI technologies evolve, protecting them through patents, trade secrets, copyrights, and trademarks has become essential for maintaining competitive advantage. However, patenting AI inventions raises complex questions about eligibility, inventor ship, and disclosure, requiring careful navigation of laws and guidelines across different jurisdictions.
How Intellectual Property Rights Apply to AI Innovations
AI innovations can be protected through multiple IP mechanisms.
- Patents protect novel AI algorithms, methods, and applications, offering exclusive rights for typically 20 years.
- Trade secrets safeguard proprietary training data, model parameters, and implementation details that provide competitive advantages.
- Copyright protects AI source code, though not underlying ideas or algorithms.
- Trademarks protect the brand names of AI products. Using trademarks along with other protections helps build strong IP portfolios that give companies a bigger competitive advantage.
Key Requirements for Patenting AI Inventions:
- Patentable Subject Matter: The AI invention must fit into legal patent categories like a process, machine, or product, and not be just an idea or formula.
- Technical Solution to a Technical Problem: It should solve a real technical problem or improve technology, such as making AI models faster or more efficient.
- Novelty: The invention must be new and not already known or published anywhere.
- Inventive Step (Non-Obviousness): It must show creativity and not be something obvious to experts in the field.
- Clear Description and Enablement: The patent must explain how the invention works so others can understand and use it.
- Clear Claim Language: The claims should be specific and focused on real technical improvements.
- Human Inventor ship: Only humans can be listed as inventors, even if AI helped in the process.
- Practical Application: The invention should show real-world use or benefits, not just a theoretical idea
When AI is Eligible and Patentable
Patent eligibility means checking if an idea or invention can legally be protected by a patent. Patentability means checking if the invention meets all the rules—like being new, useful, and inventive. AI inventions are usually eligible if they make computers work better, fix real technical issues, process data in a useful way, or improve how technology functions. They are not eligible if they only copy human thinking, use basic business ideas without any technical change, or do not clearly show how they can be used in practice. Even if an AI invention is eligible, it must also be new and not obvious.
Challenges in Drafting AI Patent Applications
Drafting effective AI patents presents unique challenges. The “black box problem” makes it hard to clearly explain how complex AI models, like neural networks, actually work, but patent rules require clear descriptions. Drafters must find the right balance between disclosure and protection–explaining enough for others to understand and reproduce the invention while keeping key details confidential.
To avoid abstract idea rejections, the patent should focus on technical improvements and practical solutions, not just algorithms or mathematical formulas. Proving that an invention is non-obvious is also tough because AI techniques quickly become common practice. Applications should explain how the system uses and processes data without revealing proprietary datasets, and include specific technical details.
Strategies for Patenting AI Innovations
To successfully patent AI inventions, focus on how your technology solves specific technical problems. Include real examples and test results that show how your invention works and why it’s better than existing solutions. When writing patent claims, create both broad claims that cover the general concept and narrow claims that describe specific details—this gives you better protection.
Keep some elements as trade secrets, especially training data, specific parameters, or implementation tricks that competitors can’t easily discover. This combination of patents and trade secrets provides stronger overall protection.
Remember that different countries have different rules. In the United States, your patent must pass the Alice framework test, which checks if your invention is more than just an abstract idea. In Europe, you must show that your invention has “technical character”—meaning it solves a real technical problem. Make sure your patent application meets the specific requirements of each country where you want protection.
The Core Challenge: Can AI Be an Inventor?
Currently, AI systems cannot be named as inventors on patent applications. Patent laws in most countries, including the United States and India, require inventors to be natural persons—meaning human beings. This rule was reinforced by key court decisions, such as in the case of Thaler v. Vidal, where attempts to list an AI system (named DABUS) as the sole inventor were rejected. The law recognizes inventorship as an intellectual act that only humans can perform, regardless of how advanced or creative an AI may be. Thus, while AI can contribute heavily towards creating inventions, it cannot be credited as an inventor under current legal frameworks.
However, humans can-and often do-use AI systems as powerful tools to assist in the inventive process. If a human works with AI to discover new ideas, create designs, or develop solutions, that person can be named as the inventor as long as they make a significant inventive contribution. For example, a human who guides an AI with specific instructions, interprets AI outputs, or combines AI-generated results with their own creative input qualifies as an inventor. The key is that the invention must involve meaningful human intellectual effort; the AI itself is seen as a tool, not an inventor. Patent applications must clearly document the human role in conceiving the invention, ensuring that inventorship laws are respected while acknowledging the growing role of AI in innovation.
USPTO AI Patent Guidelines and Recent Developments
The USPTO issued updated guidance in 2019 on patent eligibility under 35 U.S.C. § 101, which affects AI patents. The USPTO’s AI patent guidelines clarify that patent protection is possible for AI inventions, but only when they solve a specific technical problem-not just perform general tasks with AI. If someone applies for a patent, the invention must show a real improvement in technology, like better speed or accuracy, rather than repeating known methods or broad ideas.
To decide eligibility, the USPTO uses the Alice/Mayo test: first checking if the invention is just an abstract idea, such as a math formula or a mental process. If that’s the case, they look for extra details showing how the invention uses technology in concrete, practical ways-like improving a computer or another technical system.
The patent claims need to be specific about how the AI is used, and broad or vague claims will likely be rejected. Importantly, only humans-not AI systems-can be named as inventors on patents, and the human involvement must be clear in the application. The latest US guidelines also include real-world AI examples to help applicants understand what will qualify, such as AI in medical treatment customization or network security, pointing to a trend of favoring patents with clear technological advances and practical uses.
European and U.S. Patent Frameworks for AI Patents
European Patent Framework
The European Patent Office (EPO) updated its Examination Guidelines in 2025, specifically enhancing guidance on AI and machine learning (ML) inventions. The patent must involve a technical solution to a technical problem, such as a specific technical implementation or application in a particular technological field. Algorithms and mathematical methods as abstract concepts are excluded, but if integrated with technical means (like a computer to solve a technical problem), the invention becomes eligible. The updated guidelines emphasize drafting claims to highlight the AI’s role in controlling or regulating technical processes rather than merely performing abstract classifications. Human inventorship is required, and AI systems cannot be named as inventors.
U.S. Patent Framework
The United States Patent and Trademark Office (USPTO) applies the Alice/Mayo framework for determining the patent eligibility of AI inventions. AI inventions must claim a practical application rather than abstract ideas or mathematical formulas alone. To be patentable, claims must show an inventive concept beyond generic computer implementation. Like the EPO, the USPTO excludes AI systems as inventors, requiring a natural person as the named inventor. The U.S. framework focuses on ensuring that AI inventions solve a practical problem with technological application and novelty
Global Patent Trends in AI
The World Intellectual Property Organization (WIPO) recently released a Patent Landscape Report on Generative Artificial Intelligence (Gen AI), revealing some significant global patent trends.
China dominates the Gen AI patent landscape, filing nearly 70% of all patents in this domain since 2014, with over 38,000 patents contributed largely by tech giants like Tencent, Baidu, and Alibaba. Following China, the United States, South Korea, Japan, and India hold key positions in the race, with the U.S. filing around 6,300 patents, and India ranking fifth with about 1,350 patents.
The report highlights that large language models (LLMs) and generative adversarial networks (GANs) are among the most frequently patented Gen AI technologies, reflecting their wide adoption and innovation.
Leading patent holders globally include Tencent, Ping An Insurance, Baidu, and IBM, all driving the rapid development and deployment of Gen AI in diverse sectors such as life sciences, manufacturing, transportation, and telecommunications. This landscape underscores Gen AI’s transformative impact and the concentrated innovation efforts shaping its future worldwide.
India's Growing Presence in the Global AI Patent Landscape
While India may not lead the global rankings for AI patents, it has become a strong player in this fast-growing field. Between 2014 and 2023, India filed 1,350 generative AI patents, ranking fifth in the world-showing its growing influence in artificial intelligence innovation.
What’s Driving India’s AI Patent Growth?
- Government Support: The Indian government has promoted innovation through major programs like Make in India and Atmanirbhar Bharat (Self-Reliant India). These initiatives encourage Indian companies and startups to invest in research and development while protecting their inventions through patents.
- Growing Research Network: AI research in India has expanded significantly in key areas like natural language processing (NLP), smart city technology, and network optimization. Universities, research centers, engineering colleges, and startup incubators are driving important advances in AI knowledge and real-world applications.
- Partnerships and Collaboration: Cooperation between universities, businesses, and government agencies has boosted India’s patent activity. Research organizations and private companies are increasingly working together to develop advanced AI solutions and protect their innovations with patents.
- Strong Startup Culture: India’s dynamic tech startup ecosystem has become a major source of AI patents. Leading companies such as Zoho, InMobi, and Freshworks are investing heavily in AI research and development, creating innovative solutions that strengthen India’s patent portfolio.
Case Study: Thaler v. Hirshfeld
What happened?
A computer scientist named Stephen Thaler built an artificial intelligence system called DABUS. He claimed that DABUS was creative—it could come up with new ideas on its own. To prove it, Thaler filed two U.S. patent applications in 2019. He didn’t put his own name as the inventor. Instead, he listed DABUS as the inventor, saying the machine thought of the inventions without human help.
The inventions were:
- A special food container that keeps things fresh
- A flashing light that can attract attention in emergencies
USPTO’s response:
The USPTO rejected the applications. It explained that under U.S. patent law, an inventor must be a real human being, not a machine. The law uses the word “individual”, which legally means a natural person. Since DABUS is not a person, the patent applications were considered incomplete and invalid.
Court’s decision:
Thaler took the matter to court. He argued that AI should be allowed to be an inventor because it encourages innovation and reflects how modern inventions happen. The court disagreed. It said that the Patent Act clearly limits inventorship to humans. The judge also pointed out that words like “himself” and “herself” in the law prove that “individual” means a person, not a machine.
The court concluded that only people can be inventors, even if an AI helped create the idea. Policy arguments couldn’t override what the statute says. The Federal Circuit Court confirmed this ruling, and the U.S. Supreme Court later refused to review the case.
Future Trends in AI IPR Landscape
The future of AI intellectual property rights is rapidly evolving as legal systems adapt to address new challenges like who owns AI inventions and who can be named as an inventor. Countries around the world, including India, are working together to create clearer and more consistent rules for protecting and enforcing AI patents. Technology is also transforming how patents are managed. Patent offices are now using AI tools to improve patent examination and search through existing patents more efficiently. New technologies like block chain are helping make IP ownership more transparent and easier to track.
What We Infer?
AI is changing the way people create and invent new things, and intellectual property laws are trying to keep up. Right now, only humans can be named as inventors, even if AI helps in the process. In the future, laws will need to become clearer and more flexible to protect new kinds of AI inventions while still encouraging creativity and innovation.
Who are the Top 10 Companies Filing in AI Domain?
Who are the Top 10 Inventors Filing in AI domain?
Legal Status of the Patents
Legal Status of the Entire Domain (Alive vs Dead)
Top Companies vs. Year Companies Filing in AI domain?
TOP COMPANIES | EARLIEST PRIORITY YEAR | |||||
2020 | 2021 | 2022 | 2023 | 2024 | 2025 | |
SIEMENS | 2 | 3 | 5 | 3 | 2 |
|
SAVEETHA UNIVERSITY |
|
|
| 1 | 8 | 9 |
BAYER |
| 1 |
|
| 1 |
|
CMR INSTITUTE OF TECHNOLOGY |
|
|
| 2 | 6 | 1 |
SICHUAN UNIVERSITY |
| 1 | 3 | 2 | 1 | 1 |
STATE GRID CORPORATION OF CHINA | 1 | 1 | 1 | 1 | 2 | 2 |
CAMBRIDGE INSTITUTE OF TECHNOLOGY |
|
|
| 7 | 1 |
|
STATE GRID SHANGHAI MUNICIPAL ELECTRIC POWER | 1 |
|
| 2 | 3 | 2 |
NOVARTIS |
| 1 | 1 |
|
|
|
BEIJING UNIVERSITY OF TECHNOLOGY |
| 2 | 1 | 1 | 3 |
|
How are the Patents Distributed Globally?
Why MCRPL?
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