How to get a software patent for AI inventions?

Navigating Section 101 Eligibility Tests

Securing a software patent for artificial intelligence inventions requires navigating the complex landscape of Section 101 eligibility, particularly when addressing abstract ideas. Recent developments highlight that merely claiming an algorithm is insufficient; applicants must demonstrate a specific technical improvement to the computer itself. This distinction is crucial because courts often reject claims that merely automate existing processes without providing a tangible technological solution. The focus has shifted toward proving that the AI implementation solves a problem unique to computing, such as enhancing data processing speed or memory efficiency, rather than simply applying a known concept on a digital platform.

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Furthermore, the legal framework surrounding inventorship and patentability continues to evolve, with jurisdictions like the Philippines and the United Kingdom offering new precedents on AI-assisted creations. While the UK Supreme Court recently signaled a shift in how computer-implemented inventions are evaluated, the core requirement remains the demonstration of technical character. Practitioners must carefully craft claims that emphasize the specific technical contributions of the AI model, ensuring that the invention is not dismissed as an abstract idea. By aligning claims with these emerging standards, innovators can better position their AI technologies for successful patent protection, avoiding common pitfalls associated with overly broad or purely functional descriptions.

Drafting Claims For Computer Implementations

When pursuing protection for an AI-driven system, one unresolved challenge is drafting claims that clearly tie the invention to a concrete technical improvement. Recent developments, including the UK Supreme Court’s decision in Emotional Perception and updated U.S. § 101 eligibility guidance in 2025, signal that examiners and courts are looking beyond labels like “neural network” to assess whether the claimed steps solve a technical problem. Claims that merely describe automating a mental process or producing a desired output often struggle, while those that articulate how the system operates differently tend to fare better.

At AI Patent Review on patentreviewpro.com, effective claim drafting focuses on the mechanics of the implementation: how data is transformed, how model architecture or training constraints reduce latency or memory use, or how reasoning and retrieval components improve system accuracy in a measurable way. By anchoring each limitation to specific computer operations and their technical effects, applicants can present a clearer narrative of inventiveness and eligibility, even when the underlying invention involves sophisticated AI techniques.

Addressing Inventorship Requirements Globally

Inventorship remains one of the thorniest issues in securing protection for AI inventions, because nearly every jurisdiction insists that inventors be natural persons. When an AI system contributes meaningfully to the conception of an invention—whether by generating candidate architectures, optimizing training protocols, or proposing novel model configurations—applicants must carefully document the human contribution. Courts and patent offices worldwide have converged on the position that listing an AI system as an inventor renders a application invalid, as seen in the DABUS decisions across the US, UK, and Europe. The practical answer is to identify the engineers, researchers, or data scientists who directed the AI's operation, framed the problem, and selected or refined the output.

Jurisdictional nuances matter considerably. The UK Supreme Court's Emotional Perception ruling clarified that the technical character of a claimed invention, rather than the tool used to achieve it, governs patentability, easing analysis of AI-assisted subject matter. In the United States, recent guidance confirms that a natural person who makes a significant contribution to the conception qualifies, even where AI tools assisted the process. Applicants should maintain contemporaneous records showing how humans guided, verified, and integrated machine-generated results, ensuring inventorship designations withstand scrutiny while preserving eligibility under computer-implemented invention frameworks.

EPO Examination Guidelines For Software

Under EPO Guidelines, AI software is not categorically barred; the exclusion of computer programs as such means the claim must have technical character. A pure algorithm or mathematical method remains excluded, but an AI invention solving a technical problem with a concrete technical effect—for example, controlling hardware, improving image processing, reducing memory or bandwidth, or increasing diagnostic accuracy—can be patentable. Draft claims as computer-implemented methods, systems, or storage media with technical means, not as abstract models standing alone.

The unresolved drafting point is best settled by not relying on the description to supply technicality absent from the claim. At the EPO, the claimed invention as a whole must include at least one technical feature causally linked to the technical effect; training details, sensor inputs, hardware co-design, or output control can do that. State the technical problem and effect in claim language, then use dependent claims for model architecture and data processing. That framing gives AI software a defensible technical contribution without reciting the algorithm in the abstract.

UK Supreme Court Patent Shifts

The unresolved question of whether an AI system can be patented as a computer-implemented invention has been partly settled by the UK Supreme Court’s Emotional Perception decision. Rather than treating software as excluded merely because it runs on a computer, the Court looked at whether the claimed invention produces a technical effect outside the computer. For AI inventions, that means the patent application should describe a concrete technical contribution, such as improved signal processing, data handling, or control of a physical process, instead of relying on abstract model training or generic automation.

Applicants still need to show that the AI is not simply performing a mental act or business method in software form. Clear claim drafting, technical problem framing, and evidence of real-world improvement can help. The shift does not make every AI invention patentable, but it gives a clearer route for inventions where the software changes how a machine works in a measurable way.

Jurisdiction Comparison For AI Software Patents

Filing strategies differ sharply across jurisdictions, so applicants should tailor claims rather than recycle a single global draft. In the US, anchor claims to technical improvements under evolving § 101 guidance; in Europe and the UK, stress technical effects and overall contribution; in emerging markets like the Philippines, ensure human inventorship is clearly documented. A coordinated, jurisdiction-aware portfolio maximizes protection for AI inventions.