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AI Patentability: Key Differences between the U.S. and Europe

25 / 2 / 2025

Artificial intelligence (AI) is transforming industries, prompting stricter patent guidelines in both the U.S. and Europe. While both regions aim to protect innovation, they apply different criteria for AI-related patents, particularly regarding eligibility, technical contributions, and reproducibility.

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AI Patents in the U.S.: The Two-Prong Test

The U.S. Patent and Trademark Office (USPTO) follows a two-prong approach to determine AI patent eligibility:

  1. Abstract Idea Check – The invention must not be purely mathematical or a mental process.
  2. Technical Application – The AI must provide a tangible improvement, such as enhanced cybersecurity or speech recognition.

This system, based on the Alice/Mayo framework, ensures that AI patents contribute to real technological advancements rather than being overly broad or abstract.

AI Patents in Europe: Technical Purpose & Reproducibility

The European Patent Office (EPO) requires AI inventions to serve a specific technical purpose, such as improvements in image or audio processing. Additionally, applicants must provide detailed technical disclosures, including:

— Algorithmic structure – Clear descriptions of how the AI functions.

— Data characteristics – Information on the type and quality of training data.

This focus on reproducibility ensures that AI inventions are not only innovative but also practical and verifiable.

Key Differences: U.S. vs. Europe

The U.S. prioritizes practical applications, ensuring AI contributes to a technical field.

Europe demands technical specificity, requiring detailed documentation to enable reproducibility.

Both jurisdictions reject overly broad AI patents, emphasizing concrete technological improvements.

Final Thoughts

Both regions aim to protect genuine AI innovations while preventing overly broad claims. Despite their differences, both the USPTO and EPO seek to balance innovation with patent quality. AI inventors should focus on demonstrating technical contributions, practical applications, and detailed reproducibility to navigate these varying requirements successfully.

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